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pages: 337 words: 89,075

Understanding Asset Allocation: An Intuitive Approach to Maximizing Your Portfolio by Victor A. Canto

accounting loophole / creative accounting, airline deregulation, Andrei Shleifer, asset allocation, Bretton Woods, business cycle, buy and hold, buy low sell high, capital asset pricing model, commodity trading advisor, corporate governance, discounted cash flows, diversification, diversified portfolio, fixed income, frictionless, high net worth, index fund, inflation targeting, invisible hand, John Meriwether, law of one price, liquidity trap, London Interbank Offered Rate, Long Term Capital Management, low cost airline, market bubble, merger arbitrage, money market fund, new economy, passive investing, Paul Samuelson, price mechanism, purchasing power parity, risk tolerance, risk-adjusted returns, risk/return, Ronald Reagan, selection bias, shareholder value, Sharpe ratio, short selling, statistical arbitrage, stocks for the long run, survivorship bias, the market place, transaction costs, Y2K, yield curve, zero-sum game

Chapter 15 Putting It All Together: Value Timing 267 Asia Benchmark Weight Region 30% 9% International Europe 50% 30% 15% Emerging Markets 6% 20% Asset Type Style Equities 60% Size Value Large 50% 70% Growth 50% 10.5% 10.5% Value Domestic Middle 50% 50% 20% Growth World 50% 3% 3% Value 100% Small 50% 10% 1.5% Growth Curve 50% 1.5% T-Bills Domestic 20% 50% 80% 40% Fixed Income 4% T-Bonds 16% Asia 30% International 6% Europe 50% 50% 10% Emerging Markets 20% Figure 15.1 4% Strategic asset allocation. The fixed-income allocation of our global portfolio is 40 percent of total assets. Different indices can give a slightly different allocation to the different countries, but (on average) most major global indices would put the U.S. fixed-income share around 50 percent. This means 20 percent of the overall portfolio is allocated to U.S. fixed-income instruments. Within the U.S., a 20/80 split between short- and long-term bonds seems reasonable. This gives us a final allocation of 4 percent short-maturity U.S. fixed-income instruments and 16 percent long-maturity U.S. fixed-income instruments. Again, within most indices, the rest-of-the-world breakdown is 50 percent Europe, 30 percent Asia, and 20 percent emerging markets.

(In principle, the allocation to international stocks could be further subdivided by country, size, and style, but we ignore this subdivision for the time being.) Conventional wisdom and approximate market values suggest 10 percent is a good proxy for the short-term fixed-income share of the total fixed-income market value. Given our portfolio’s 40 percent allocation to fixed income, it follows we allocate 4 percent to short-term instruments and 36 percent to longer-maturity instruments. (We could further disaggregate the longer-term fixed-income instruments into a global allocation, but for this exercise, we stay domestic.) Figure 6.3 illustrates the SAA produced by my interpretation of the various asset classes’ market weights. Either exchange-traded funds (ETFs), or passively managed low-cost index funds, could fill most buckets in question.

The tilts can be easily described: The strategy increased the exposure to U.S. equities at the fixed-income instruments’ expense. Despite the lower allocation to fixed income, the CAA process also increased the allocation to cash. A way of interpreting this result is that the CAA process called for a reduction in the duration of the fixed-income portfolio. Within the style allocation, the tilts favored value stocks, and within the size allocation, the tilts favored mid- and small-cap stocks. The sole domestic underweighting came with large-cap growth stocks. By combining the overweights and underweights in Figure 7.3 with the links between the economic drivers and asset choices in Figure 7.1, one can reverseengineer the process and make inferences about the implicit forecast in the CAA strategy sample. The message is quite simple: The allocations were bearish on fixed income and bullish on all equities except large-cap growth stocks, to which there was an almost neutral allocation.


All About Asset Allocation, Second Edition by Richard Ferri

activist fund / activist shareholder / activist investor, asset allocation, asset-backed security, barriers to entry, Bernie Madoff, buy and hold, capital controls, commoditize, commodity trading advisor, correlation coefficient, Daniel Kahneman / Amos Tversky, diversification, diversified portfolio, equity premium, estate planning, financial independence, fixed income, full employment, high net worth, Home mortgage interest deduction, implied volatility, index fund, intangible asset, Long Term Capital Management, Mason jar, money market fund, mortgage tax deduction, passive income, pattern recognition, random walk, Richard Thaler, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, selection bias, Sharpe ratio, stocks for the long run, survivorship bias, too big to fail, transaction costs, Vanguard fund, yield curve

VWEHX Actively managed B–BB grade IGOV Japan is 25% of the fund EMB BB rated bonds VWITX VMLTX Actively managed, 6–12 years Actively managed, 2–6 years Fixed-Income Investments 169 CHAPTER SUMMARY A well-diversified portfolio contains both fixed-income and equity investments. To obtain maximum benefit, the fixed-income portion of the portfolio should also be broadly diversified into several different fixed-income categories and rebalanced annually. Asset allocation of fixed-income investments leads to higher overall returns with little increase in portfolio risk. There is no lack of diversification potential in the bond market. Fixed-income asset subclasses include government bonds, corporate bonds, home mortgage pools, asset-backed bonds such as those backed by credit card receivables, and foreign developed and emerging markets. A total bond market fund covers most investment-grade fixed-income securities. The best way to build the fixed-income portion of a portfolio is through low-cost bond mutual funds, particularly bond index funds.

.: Princeton University Press, 2002). This page intentionally left blank CHAPTER 8 Fixed-Income Investments KEY CONCEPTS ● ● ● ● There are several fixed-income categories to invest in. Different categories exhibit unique risks and returns. A diversified fixed-income portfolio enhances return. Low-cost bond mutual funds are an ideal way to invest. There is no lack of diversification potential in the bond market. Fixed-income categories abound with unique investment opportunities. They include government bonds, investment-grade and high-yield corporate bonds, mortgage-backed bonds, asset-backed securities, and foreign debt. Using a broadly diversified fixedincome strategy can increase portfolio return without additional risk. Fixed-income asset allocation is often overlooked in the investment advice industry.

Books and articles on asset allocation tend to devote a significant amount of time to the benefits of equity asset diversification while largely ignoring fixed-income selection. It is common for investment managers to place their clients’ entire fixed-income allocation in government bonds only and ignore all other fixed-income categories. Those advisors tell clients that they “prefer to take their risk on the stock side.” I tend to believe that they use only government bonds to make the advisor’s 147 CHAPTER 8 148 job easy rather than to go through the extra work to create a properly diversified fixed-income allocation. Investors should always use low-cost mutual funds in categories that would otherwise require significant analysis and expertise, such as high-yield corporate bonds and foreign bonds. The simplest way to gain instant fixed-income diversification is through a low-cost bond index fund or ETF.


pages: 317 words: 106,130

The New Science of Asset Allocation: Risk Management in a Multi-Asset World by Thomas Schneeweis, Garry B. Crowder, Hossein Kazemi

asset allocation, backtesting, Bernie Madoff, Black Swan, business cycle, buy and hold, capital asset pricing model, collateralized debt obligation, commodity trading advisor, correlation coefficient, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, diversified portfolio, fixed income, high net worth, implied volatility, index fund, interest rate swap, invisible hand, market microstructure, merger arbitrage, moral hazard, Myron Scholes, passive investing, Richard Feynman, Richard Feynman: Challenger O-ring, risk tolerance, risk-adjusted returns, risk/return, selection bias, Sharpe ratio, short selling, statistical model, stocks for the long run, survivorship bias, systematic trading, technology bubble, the market place, Thomas Kuhn: the structure of scientific revolutions, transaction costs, value at risk, yield curve, zero-sum game

World Investment Opportunities Traditional Investments Modern Alternatives Traditional Alternatives Stocks Private Equity Hedge Funds Bonds Real Estate Managed Futures Commodities EXHIBIT 4.3 Traditional and Alternative Asset Class Breakdown 66 THE NEW SCIENCE OF ASSET ALLOCATION Primary Asset Classes ■ Traditional Assets ■ Equity Domestic Investment International Non Domestic Emerging Markets ■ Fixed Income Government Corporate Corporate High-Yield ■ Traditional Alternative Investments ■ Private Equity ■ Commodities ■ Real Estate ■ Modern Alternative Investments ■ Hedge Funds ■ Managed Futures (CTAs) The list of investment benchmarks used to represent the above asset classes is described in the glossary.10 In the following section, the benchmarks used to represent the above investment areas are as follows: Domestic Investment (the Russell 1000 and Russell 2000); International NonDomestic (MSCI EAFE); Emerging Markets (MSCI Emerging Markets); Fixed Income Government (Barclays Capital U.S. Government); Fixed Income Aggregate (Barclays Capital U.S. Aggregate); Fixed Income High Yield (Barclays Capital U.S. Corporate High Yield); Private Equity (Index of publicly traded private equity); Commodities (S&P Goldman Sachs Commodity Index); Real Estate (FTSE NAREIT All REIT); Hedge Funds (CASAM/CISDM Equal Weight Hedge Fund Index); and Managed Futures (CASAM/CISDM CTA Equal Weight Index).

Exhibit 4.13 indicates that when returns are ranked on the S&P 500, (1) equity sensitive investments (stock and private equity) perform poorly in the worst 72 months of the S&P 500; (2) high-yield corporate bonds, hedge funds, and real estate also reported moderate negative returns in the worst 72 months of the S&P 500; and (3) commodities, non-credit sensitive fixed income, and CTAs had small negative to positive returns. Results reversed in the best 72 S&P 500 months; that is, equity sensitive assets performed well while less equity sensitive assets had less positive returns. In contrast, results in Exhibit 4.14, when returns are ranked on the BarCap U.S. Aggregate Bond Index, fixed income based securities did poorly in down fixed income markets while most equity based investments as well as modern alternatives reported positive returns. Portfolio returns reflect these individual investment results. As shown in Exhibit 4.15, in periods of extreme negative S&P 500 returns, aggressive portfolios performed worse than more conservative portfolios.

The difference between the performance of first quartile large cap funds and third quartile large cap funds was 2.73% per year from 2003 to 2008. For small cap funds the difference is 4.1%. Similar results are obtained for fixed income funds and international equity funds. These results indicate that it does not pay to waste time, money, and effort on finding alpha or top managers in the area of traditional equity and fixed income investments. Not only do most managers fail to beat their benchmarks, even when an investor gets lucky and finds a “good” manager, he fails to outperform other managers by a significant amount. While the return differential between top and bottom quartile equity and fixed income managers is relatively small, the same cannot be said for alternative investment managers. For instance, according to a report by Yale endowment (Yale Endowment Report, 2005), the return differential between the first quartile venture capital funds and third quartile venture capital funds was 43.2% for 1995 to 2005.


pages: 504 words: 139,137

Efficiently Inefficient: How Smart Money Invests and Market Prices Are Determined by Lasse Heje Pedersen

activist fund / activist shareholder / activist investor, algorithmic trading, Andrei Shleifer, asset allocation, backtesting, bank run, banking crisis, barriers to entry, Black-Scholes formula, Brownian motion, business cycle, buy and hold, buy low sell high, capital asset pricing model, commodity trading advisor, conceptual framework, corporate governance, credit crunch, Credit Default Swap, currency peg, David Ricardo: comparative advantage, declining real wages, discounted cash flows, diversification, diversified portfolio, Emanuel Derman, equity premium, Eugene Fama: efficient market hypothesis, fixed income, Flash crash, floating exchange rates, frictionless, frictionless market, Gordon Gekko, implied volatility, index arbitrage, index fund, interest rate swap, late capitalism, law of one price, Long Term Capital Management, margin call, market clearing, market design, market friction, merger arbitrage, money market fund, mortgage debt, Myron Scholes, New Journalism, paper trading, passive investing, price discovery process, price stability, purchasing power parity, quantitative easing, quantitative trading / quantitative finance, random walk, Renaissance Technologies, Richard Thaler, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, selection bias, shareholder value, Sharpe ratio, short selling, sovereign wealth fund, statistical arbitrage, statistical model, stocks for the long run, stocks for the long term, survivorship bias, systematic trading, technology bubble, time value of money, total factor productivity, transaction costs, value at risk, Vanguard fund, yield curve, zero-coupon bond

CHAPTER 14 Fixed-Income Arbitrage Trading on fixed-income arbitrage is like picking up nickels in front of a steamroller. —Saying among traders The global fixed-income markets are vast in terms of the value of outstanding bonds, the turnover of these bonds, and the size of the related derivatives markets. The most important fixed-income market is the government bond market, followed by the markets for corporate bonds and mortgage bonds. The key derivatives markets include bond futures, interest-rate swaps, credit default swaps, options, and swaptions, which give the option to enter into an interest-rate swap. Almost all bond prices depend heavily on the risk-free interest rate, so there is significant co-movement among bond yields and bond returns. Therefore, fixed-income arbitrage traders often trade on the relative value among fixed-income securities to exploit price differences among closely related securities.

The idea of how clienteles arise in markets and how intermediaries make them appear seamless are a fascinating part of the fixed-income market, which is mostly an institutional market. Also, fixed income has many embedded options and convexity issues—I was attracted to these complicated models. Many entities do not wish to hold instruments that have these embedded options, or a wish to reduce the convexity risk. They sell it off. As a result, there’s an opportunity for investors who understand convexity and convexity hedging to intermediate in the market and assume and carry the risk forward in time. LHP: So, at the high level, fixed-income arbitrage traders intermediate between clienteles and accommodate convexity hedging. Can you talk more specifically about some of the fixed-income arbitrage trades? MS: Yes, fixed-income arbitrage is intermediating supply and demand imbalances that result from flows in the marketplace.

Arbitrage Strategies Turning to arbitrage strategies, these consist of fixed-income arbitrage, convertible bond arbitrage, and event-driven investment. Fixed-income arbitrage is based on a number of so-called convergence trades. In a convergence trade, you look for similar securities with different prices; then you buy low, sell high, and hope for convergence. Since fixed-income securities usually have a finite maturity, convergence must eventually happen, but the sooner it happens, the more profitable the trade. The biggest risk in convergence trades is that the trader is forced to unwind the trade when the price gap widens and the trade loses money. The economist (and trader!) John Maynard Keynes expressed this risk well: The markets can remain irrational longer than you can remain solvent. Typical examples of fixed-income arbitrage trades include on-the-run versus off-the-run Treasury bonds, yield curve trading, betting on swap spreads, mortgage trades, futures-bond basis trades, and trades on the basis between bonds and credit default swaps (CDS).


pages: 224 words: 13,238

Electronic and Algorithmic Trading Technology: The Complete Guide by Kendall Kim

algorithmic trading, automated trading system, backtesting, commoditize, computerized trading, corporate governance, Credit Default Swap, diversification, en.wikipedia.org, family office, financial innovation, fixed income, index arbitrage, index fund, interest rate swap, linked data, market fragmentation, money market fund, natural language processing, quantitative trading / quantitative finance, random walk, risk tolerance, risk-adjusted returns, short selling, statistical arbitrage, Steven Levy, transaction costs, yield curve

Currently, the focus on client-to-dealer market trading has turned to credit markets as Thomson’s TradeWeb forces its way into corporate bond markets to compete directly with MarketAxess. TradeWeb is the current market leader in liquid fixed-income products such as treasuries, but MarketAxess is the dominant player in illiquid markets. Fixed-income platforms are also moving into derivatives with most of the attention focused on interest rate swaps and credit derivatives (see Exhibit 11.7). Other trading venues such as algorithmic trading are still immature in market penetration for fixed-income instruments, with a growing number of firms looking to gain access to historical transaction data for analysis. Liquid fixed-income markets should benefit greatly from this opportunity. U.S. corporate debt and their derivatives have become one of the fastestgrowing segments of the U.S. fixed-income market. By 2006, the total notional outstanding credit derivatives market is expected to reach US $8.5–9.0 trillion.

‘‘The most effective and complex algorithm is the human,’’ according to Kevin Bourne, global head of execution trading at HSBC. News-reading technologies should have reached the market by the end of 2006. 6.7 Black Box Trading for Fixed-Income Instruments The feasibility of utilizing an algorithm for fixed-income instruments seems theoretical for the time being. Most electronic trades are executed via a request for quote (RFQ) venue where customers or other dealers retain the ability to refuse a trade request. Fixed-income instruments are also primarily a dealer market. Most algorithms rely on a constant stream of market data, which is not currently available for fixed income markets. Few transactions are posted through a black box because there are few bond trading platforms that provide the necessary liquidity. Currently, the U.S. Treasury market is dominated by eSpeed and Icap where opportunistic traders attempt to arbitrage their positions through purchasing an instrument on one platform and selling it via another.

The equities markets will execute trades using some sort of algorithmic model, but the same will most likely be true for other products such as futures, options, and foreign exchange. Fixed income will be one of the last to move along because it is predominantly a dealer market, but when it does, the first asset class will most likely be the most liquid sectors such as the U.S. Treasury market. The later arrival of electronic trading in fixed-income markets compared to equities reflects distinct differences between the two. Fixed-income products are far less homogenous, with many more separate and individually less liquid issues than equities. This makes it technically difficult and more expensive to introduce automated systems. There are millions of Fixed-income instruments on issue in the United States alone (see Exhibit 11.1) with different coupon rates, maturities, with varying frequency of interest payments, etc., compared to a few thousand listed shares.


pages: 289 words: 113,211

A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation by Richard Bookstaber

"Robert Solow", affirmative action, Albert Einstein, asset allocation, backtesting, beat the dealer, Black Swan, Black-Scholes formula, Bonfire of the Vanities, butterfly effect, commoditize, commodity trading advisor, computer age, computerized trading, disintermediation, diversification, double entry bookkeeping, Edward Lorenz: Chaos theory, Edward Thorp, family office, financial innovation, fixed income, frictionless, frictionless market, George Akerlof, implied volatility, index arbitrage, intangible asset, Jeff Bezos, John Meriwether, London Interbank Offered Rate, Long Term Capital Management, loose coupling, margin call, market bubble, market design, merger arbitrage, Mexican peso crisis / tequila crisis, moral hazard, Myron Scholes, new economy, Nick Leeson, oil shock, Paul Samuelson, Pierre-Simon Laplace, quantitative trading / quantitative finance, random walk, Renaissance Technologies, risk tolerance, risk/return, Robert Shiller, Robert Shiller, rolodex, Saturday Night Live, selection bias, shareholder value, short selling, Silicon Valley, statistical arbitrage, The Market for Lemons, time value of money, too big to fail, transaction costs, tulip mania, uranium enrichment, William Langewiesche, yield curve, zero-coupon bond, zero-sum game

The firm’s investment bankers lorded over that sexy part of the business, but I was headed for the fixed income division—bonds. You couldn’t get less glamorous than fixed income—unless, of course, you worked in fixed income research (FIR), which is exactly where I would spend my first years on Wall Street. Bob Platt wanted to change all that. A former midlevel insurance executive, he had been snatched from obscurity to run Morgan Stanley’s fixed income research division. Obscurity in this case was the giant institutional machine called the Equitable Life Insurance Company, headquartered at 52nd Street and Seventh Avenue, not far from Morgan Stanley’s offices at 50th Street and Sixth. When Bob arrived at Morgan Stanley in 7 ccc_demon_007-032_ch02.qxd 2/13/07 A DEMON 1:44 PM OF Page 8 OUR OWN DESIGN 1982, the fixed income domain was still just a step or two removed from the backwater of green-eyeshaded bookkeepers, ledgers stacked on their Steelcase desks, tracking bond coupon payments.

CRUNCH TIME AT MORGAN STANLEY The job of the quants descending on Wall Street was to exploit the relationships along the yield curve, to develop mathematical models that would tease a higher return out of a bond portfolio or a bond trading operation than the green-eyeshade gang could. By the early 1980s, a number of other firms were already riding the number crunching wave. Marty Leibowitz at Salomon had built a strong team that was at the top of the heap for fixed income portfolio strategy and yield-curve trading. This group would provide the raw material for Salomon’s gold rush into proprietary fixed income trading a few years later. At Morgan Stanley, Platt wanted to use fixed income research to scale another mountain. An opera aficionado who fancied himself a Brahmin intellectual, he was uncomfortable in the ranks of the meat-and-potatoes bonds crowd. His vision for fixed income research was to slide it away from backwater trader support and propel it into an investment banking role, where the prestige was. The idea, as Bob laid it out to me several times, was to create an investment bank within an investment bank.

But success with equities involves more than trading ability and risk taking. THE PROBLEM WITH STOCKS Profitability in equity trading requires a more complex business structure than is required for fixed income. In the fixed income markets substantial profits can be made simply through the bid/offer spread. For the higherrisk and less liquid bonds such as junk bonds and emerging market bonds, the spread can be as wide as one or two points. Similarly, while the agency instruments in the mortgage market trade with eighth- and sixteenth-of-apoint spreads, the derivative instruments—collateralized mortgage obligations (CMOs), IOs, and POs—can have spreads that are multiples of those. In contrast to the fixed income market, where a firm takes a principal position, transacts in large volume, and extracts a spread for the inventory and market making service it provides, equity trades generally move through the conduit of an exchange that takes over these functions.


pages: 701 words: 199,010

The Crisis of Crowding: Quant Copycats, Ugly Models, and the New Crash Normal by Ludwig B. Chincarini

affirmative action, asset-backed security, automated trading system, bank run, banking crisis, Basel III, Bernie Madoff, Black-Scholes formula, business cycle, buttonwood tree, Carmen Reinhart, central bank independence, collapse of Lehman Brothers, collateralized debt obligation, collective bargaining, corporate governance, correlation coefficient, Credit Default Swap, credit default swaps / collateralized debt obligations, delta neutral, discounted cash flows, diversification, diversified portfolio, family office, financial innovation, financial intermediation, fixed income, Flash crash, full employment, Gini coefficient, high net worth, hindsight bias, housing crisis, implied volatility, income inequality, interest rate derivative, interest rate swap, John Meriwether, Kickstarter, liquidity trap, London Interbank Offered Rate, Long Term Capital Management, low skilled workers, margin call, market design, market fundamentalism, merger arbitrage, Mexican peso crisis / tequila crisis, Mitch Kapor, money market fund, moral hazard, mortgage debt, Myron Scholes, negative equity, Northern Rock, Occupy movement, oil shock, price stability, quantitative easing, quantitative hedge fund, quantitative trading / quantitative finance, Ralph Waldo Emerson, regulatory arbitrage, Renaissance Technologies, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Shiller, Ronald Reagan, Sam Peltzman, Sharpe ratio, short selling, sovereign wealth fund, speech recognition, statistical arbitrage, statistical model, survivorship bias, systematic trading, The Great Moderation, too big to fail, transaction costs, value at risk, yield curve, zero-coupon bond

Lehman Brothers believed that its presence in the global capital markets; its access to advanced information technology, in-depth market research, proprietary risk management, and its general assessment experience under rapidly changing market conditions gave it a comparative advantage in finding profitable trading opportunities. Fixed Income Fixed income is another large part of the capital markets division. Fixed income was particularly important at Lehman Brothers, which was known as one of the leading fixed-income specialists in investment banking. Fixed-income instruments pay a fixed, known stream of future income—hence the term “fixed income.” Bonds are the most common example. Buy a stock, and you have no idea what the future returns will be. The stock could go up or down by any amount, making the income from it variable, not fixed. Bonds and other fixed-income instruments, by contrast, commit to paying a known payment on specified future dates.5 As a broker, Lehman helped investors trade fixed-income instruments, 24 hours a day and around the world. The fixed-income area had several subdivisions.

The financial system is fundamentally linked through this web of connections. Fixed-Income Derivatives The fixed-income derivatives group created, traded, made markets, and invested in the derivatives that are based on the underlying value of fixed-income products, including swaps, options, and futures. This area also included highly levered CDO and CDS fixed-income derivatives, which were based on underlying mortgages. Lehman lost a lot of money on these derivatives. Lehman Brothers Bank Lehman owned an actual bank, Lehman Brothers Bank. Like most other banks, it issued mortgages for commercial and residential real estate. Lehman believed that owning a bank let it move more easily into the mortgage securitization business, but the bank was also outside Lehman’s core expertise. Foreign Exchange Lehman operated in global equity and fixed-income markets, so its clients needed foreign currency transactions.

Myron Scholes, a PhD from the University of Chicago and a professor at MIT and Chicago, became a managing director of Salomon in 1991, as well as co-head of the fixed-income sales and trading department. Finally Robert Merton, a PhD from MIT and a Harvard professor, arrived in 1988 as a senior advisor to Salomon Brothers. The whole quantitative team worked in fixed income, but focused on slightly different areas. Haghani was a bond arbitrage trader, Hawkins worked in bond arbitrage and mortgages, Hilibrand worked in bond arbitrage, Hufschmid worked on the UK fixed-income arbitrage desk and then moved permanently to the FX trading desk, Krasker worked in fixed-income arbitrage, Krisnamacher worked on the derivatives trading desk, Leahy was head of mortgage trading, and Rosenfeld was the co-head of the bond arbitrage group.


pages: 490 words: 117,629

Unconventional Success: A Fundamental Approach to Personal Investment by David F. Swensen

asset allocation, asset-backed security, buy and hold, capital controls, cognitive dissonance, corporate governance, diversification, diversified portfolio, fixed income, index fund, law of one price, Long Term Capital Management, market bubble, market clearing, market fundamentalism, money market fund, passive investing, Paul Samuelson, pez dispenser, price mechanism, profit maximization, profit motive, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Shiller, shareholder value, Silicon Valley, Steve Ballmer, stocks for the long run, survivorship bias, technology bubble, the market place, transaction costs, Vanguard fund, yield curve, zero-sum game

The answer to the asymmetry no doubt lies in the superior sophistication of issuers of debt relative to the limited market savvy of purchasers of debt. In point of fact, fixed-income markets attract analysts several notches below the quality and sophistication of equity analysts, even though the complexity of the task facing the fixed-income analyst arguably exceeds the difficulty of the equity analyst’s job. Corporate bond investors need familiarity not only with the complexities of fixed-income markets, but also with the full range of issues involved in equity valuation. Since understanding the cushion provided by a company’s equity proves essential in evaluating a corporation’s ability to service debt, bond analysts require a full assessment of a company’s stock price. Ironically, because financial rewards for successful equity analysis far outstrip the rewards for successful fixed-income analysis, the talent gravitates to the easier job of simply analyzing equity securities.

If financial engineers face challenges in getting the option pricing right, what chance do individual investors have? Optionality proves even more difficult to assess than credit risk. In the case of fixed-income instruments with credit risk, sensible investors look at bond yields with skepticism, knowing that part of the return may be lost to corporate downgrades or defaults. In the case of fixed-income instruments with high degrees of optionality, everyday investors hold no clue as to the appropriate amount by which to discount stated yields to adjust for the possible costs of the options. In fact, many professionals fail to understand the difficult dynamics of fixed-income options. Piper Capital’s Worth Bruntjen In a celebrated case of the early 1990s, Worth Bruntjen, a fixed-income specialist at Piper Capital in Minneapolis, built an enormous reputation as a manager of mortgage-backed securities portfolios.

Investors pursuing strategies that fail the third criterion (that is, by investing in narrow, shallow, uninvestable niches) deserve their fate. Fixed-income alternatives dominate the population of well-defined markets that serve no valuable portfolio role. While default-free, noncallable, full-faith-and-credit obligations of the U.S. government play a basic, valuable, differentiable role in investor portfolios, investment-grade corporate bonds, high-yield bonds, foreign bonds, and asset-backed securities contain unattractive characteristics that argue against inclusion in well-constructed portfolios. Understanding the shortcomings of particular fixed-income investment alternatives, particularly in regard to how those alternatives relate to the objectives of the fixed-income asset class, helps investors in making well-informed portfolio decisions. Those asset classes that require superior active management results to produce acceptable risk-adjusted returns belong only in the portfolios of the handful of investors with the resources and fortitude to pursue and maintain a high-quality active investment management program.


pages: 385 words: 128,358

Inside the House of Money: Top Hedge Fund Traders on Profiting in a Global Market by Steven Drobny

Albert Einstein, asset allocation, Berlin Wall, Bonfire of the Vanities, Bretton Woods, business cycle, buy and hold, buy low sell high, capital controls, central bank independence, commoditize, commodity trading advisor, corporate governance, correlation coefficient, Credit Default Swap, diversification, diversified portfolio, family office, fixed income, glass ceiling, high batting average, implied volatility, index fund, inflation targeting, interest rate derivative, inventory management, John Meriwether, Long Term Capital Management, margin call, market bubble, Maui Hawaii, Mexican peso crisis / tequila crisis, moral hazard, Myron Scholes, new economy, Nick Leeson, oil shale / tar sands, oil shock, out of africa, paper trading, Paul Samuelson, Peter Thiel, price anchoring, purchasing power parity, reserve currency, risk tolerance, risk-adjusted returns, risk/return, rolodex, Sharpe ratio, short selling, Silicon Valley, The Wisdom of Crowds, too big to fail, transaction costs, value at risk, yield curve, zero-coupon bond, zero-sum game

The next big asset category where we can be systematic, earn risk premia, and control our downside is fixed income. In Triumph of the Optimist (by Elroy Dimson, Paul Marsh, and Mike Staunton), a book about risk premia around the world, there is a whole section on bonds. Because bonds, on average, have paid a positive risk premium over time, you are supposed to be long fixed income. They don’t pay the same as equities, but they shouldn’t because they aren’t as risky as equities. But that’s the beauty of 62 INSIDE THE HOUSE OF MONEY being able to take on leverage.When we allocate 20 percent of our risk to fixed income, it doesn’t mean we only put 20 percent of our assets into fixed income.There are all kinds of interesting things you can do in fixed income with leverage and still only utilize 20 percent of your capital. For example, you could put 40 percent of your capital into shorterduration bonds.When using leverage, you want the highest Sharpe ratio because you’re borrowing money against your investment, and the best Sharpe ratios are found in the two years and under the sector of fixed income.

It’s a simple trade and it’s liquid.When I see dislocation in the direction of pain to the U.S. economy, I buy Eurodollars—it’s not brain surgery. 82 INSIDE THE HOUSE OF MONEY I remember having a disagreement with a guy in Goldman’s risk unit during the big rate-cutting cycle post-2000 in the United States. He said,“Why are you guys always long Eurodollars? Why don’t you have some South American fixed income, something in Asia, some diversification?” My reply was, “When the Fed is in an aggressive rate-cutting mode I want to be long Eurodollars because it’s the most obvious trade in the most liquid market in the world. I don’t want to be long South American fixed income or anything else when there is a clear trend in a liquid market.” (See Figure 5.4.) Over your trading career, have you made more money in fixed income from the long or short side? Long, and again that makes perfect sense when you look at how markets trade. Bear markets in fixed income are very short with powerful rallies. You can make money during a bear market but you have to time your trades perfectly.

As a medium-term player, I would expect generally to make money in a rallying market.Also, being long fixed income is a synthetic long gamma trade. More than 90 percent of the time, if there is a major dislocation to the economy, fixed income will rally. I sleep better at night knowing that. 98.50 7 97.50 97.00 Fed Funds (%) 5 96.50 4 96.00 95.50 3 Fed Funds Eurodollar Futures 95.00 2 94.50 FIGURE 5.4 -0 1 De c 01 v- 1 Fed Funds and Eurodollar Futures, 2001 Source: Bloomberg. No -0 Oc t 1 -0 Se p 1 -0 1 Au g Ju l-0 1 01 Ju n- -0 ay M Ap r-0 1 M ar b- 01 -0 1 94.00 Fe Ja n- 01 1 Price (100 minus Price Equals Implied Yield) 98.00 6 THE PROP TRADER 83 There are other trades where you can make money in a fixed income bear market, such as currencies. There are often great opportunities in the foreign exchange markets when you start getting bear fixed income markets.


pages: 620 words: 214,639

House of Cards: A Tale of Hubris and Wretched Excess on Wall Street by William D. Cohan

asset-backed security, call centre, collateralized debt obligation, corporate governance, corporate raider, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Deng Xiaoping, diversification, Financial Instability Hypothesis, fixed income, Hyman Minsky, Irwin Jacobs, John Meriwether, Long Term Capital Management, margin call, merger arbitrage, money market fund, moral hazard, mortgage debt, mutually assured destruction, Myron Scholes, New Journalism, Northern Rock, Renaissance Technologies, Rod Stewart played at Stephen Schwarzman birthday party, savings glut, shareholder value, sovereign wealth fund, too big to fail, traveling salesman, Y2K, yield curve

The performance of every one of the firm's major divisions— investment banking, clearing, asset management, and institutional equities—was down meaningfully from the third quarter of the year before, with one exception: fixed income. Net revenues for fixed income were $416.1 million, up 78.4 percent from $233.3 million in the previous year's third quarter. “Although down from last quarter's record results, fixed income revenues remained strong year-over-year, with solid performances in the mortgage-backed securities, high yield and credit derivatives areas,” the firm announced. In short order, Bear Stearns's fixed-income division accounted for one-third of the firm's revenues in the first nine months of 2001, up from 18 percent in the first nine months of 2000. On October 18, the Wall Street Journal reported that Bear Stearns would be joining the ranks of other Wall Street firms in cutting 830 jobs, or 7.5 percent of its workforce of 11,147 employees.

“Mortgage-backed securities revenues increased significantly as residential mortgage refinancing activity reached record levels during the year, driving record new issue activity, and demand for high-quality fixed income investments continued.” The firm did not break out separately the profitability of Spector's fixed-income division, but the overall grouping of investment banking (Schwartz's bailiwick), institutional equities, and fixed income had increased its pretax income to $2 billion in 2004, from $1.3 billion in 2002, and it would be safe to say that much of the increase in the pretax income came from the growth in the fixed-income division. Slowly but surely the market and the press began to naturally assume that Spector was Cayne's heir apparent, since he ran such a substantial portion of the firm's businesses.

For Sharon, the conversation with Cioffi about the Enzo “was probably the beginning of the end, when Ralph's thinking about buying million-dollar Ferraris.” He contemplated buying a partnership stake in a Gulfstream jet and was the executive producer of the 2006 independent film Just Like My Son, starring Rosie Perez. CAYNE CAPS SPECTOR y 2004, there was no question that the businesses at the firm that reported to Warren Spector—fixed income, institutional equities, and asset management—were driving the growth of the firm. Particularly important was the exponential growth of the fixed-income business, which was without question Spector's fiefdom. Fixed-income revenue in 2004 was $3.1 billion—nearly 45 percent of the firm's overall revenue of $6.8 billion—and had increased some 63 percent, from $1.9 billion in revenues, since 2002. “These businesses benefited from the low level of interest rates, a steep yield curve and narrowing of corporate credit spreads,” the firm reported in its SEC filings.


pages: 313 words: 101,403

My Life as a Quant: Reflections on Physics and Finance by Emanuel Derman

Berlin Wall, bioinformatics, Black-Scholes formula, Brownian motion, buy and hold, capital asset pricing model, Claude Shannon: information theory, Donald Knuth, Emanuel Derman, fixed income, Gödel, Escher, Bach, haute couture, hiring and firing, implied volatility, interest rate derivative, Jeff Bezos, John Meriwether, John von Neumann, law of one price, linked data, Long Term Capital Management, moral hazard, Murray Gell-Mann, Myron Scholes, Paul Samuelson, pre–internet, publish or perish, quantitative trading / quantitative finance, Sharpe ratio, statistical arbitrage, statistical model, Stephen Hawking, Steve Jobs, stochastic volatility, technology bubble, the new new thing, transaction costs, volatility smile, Y2K, yield curve, zero-coupon bond, zero-sum game

Though I did ultimately improve the model, the traders benefited most from the friendly user interface I programmed into it.This simple ergonomic change had a far greater impact on their business than the removal of minor inconsistencies; now they could handle many more client requests for business. Although options theory originated in the world of stocks, it is exploited more widely in the fixed-income universe. Stocks (at least at first glance) lack mathematical detail-if you own a share of stock you are guaranteed nothing; all you really know is that its price may go up or down. In contrast, fixed-income securities such as bonds are ornate mechanisms that promise to spin off future periodic payments of interest and a final return of principal. This specification of detail makes fixed income a much more numerate business than equities, and one much more amenable to mathematical analysis. Every fixed-income securitybonds, mortgages, convertible bonds, and swaps, to name only a few-has a value that it depends on, and is therefore conveniently viewed as a derivative of the market's underlying interest rates.

In contrast, quants have been a rarer presence in the equity world. There, most investors are concerned with which stock to buy, a problem on which the advanced mathematics of derivatives can shed little light. Fixed income and equities have fundamentally different foci. When you walk around a frenetic fixed-income trading floor, you hear people shouting out numbers-yields and spreads-over the hoot-andholler; on a busy equities floor, you mostly hear people shouting company names. Fixed-income trading requires a better grasp of technology and quantitative methods than equities trading. A trader friend of mine summed it up succinctly when, after I commented to him that the fixed-income traders I knew seemed smarter than the equity traders, he replied that "that's because there's no competitive edge to being smart in the equities business" I don't mean to suggest that all quants work on the Black-Scholes model.

A year or so after joining O'Connor, he departed together with two software engineers he had met there to start a company to produce fixed-income risk management software. They based themselves in Chicago and called their firm RMS, an evocative name that I greatly admired.' David's plan to build a commercial fixed-income risk management system was an inspired one, several years ahead of its time. Although many trading firms and investment banks, including Goldman, wrote their own risk-management software, at that time no one had yet marketed that type of product commercially. Stan Diller at Bear Stearns was pushing in that direction; as head of FAST, their fixed-income research group, he was building a system called AutoBond, which was intended to first be used by the trading desks and then, once polished and debugged, to be sold to clients.


pages: 258 words: 71,880

Street Fighters: The Last 72 Hours of Bear Stearns, the Toughest Firm on Wall Street by Kate Kelly

bank run, buy and hold, collateralized debt obligation, corporate governance, corporate raider, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Donald Trump, fixed income, housing crisis, index arbitrage, Long Term Capital Management, margin call, moral hazard, quantitative hedge fund, Renaissance Technologies, risk-adjusted returns, shareholder value, technology bubble, too big to fail, traveling salesman

http://us.penguingroup.com To the 14,000 people who worked at Bear Stearns CAST OF CHARACTERS At The Bear Stearns Companies Alan Schwartz, chief executive Sam Molinaro, chief financial officer Bob Upton, treasurer Tom Marano, head of mortgages Paul Friedman, chief operating officer of the fixed-income division Jimmy Cayne, chairman Alan “Ace” Greenberg, director and former CEO Vincent Tese, lead director Richie Metrick, investment banker Carl Glickman, director Tim Greene, cohead of the fixed-income funding desk Steve Meyer, cochief of the equities division Pat Lewis, deputy treasurer Jeff Mayer, cohead of the fixed-income division David Kim, internal lawyer Steve Begleiter, head of corporate strategy At JPMorgan Chase & Co. Jamie Dimon, chairman and CEO Steve Black, cochief of the investment bank Bill Winters, cochief of the investment bank Matt Zames, head of foreign-exchange and interest-rate product trading Steve Cutler, general counsel Doug Braunstein, head of corporate finance At the Federal Reserve Tim Geithner, president of Federal Reserve Bank of New York Ben Bernanke, chairman of the Federal Reserve Board Kevin Warsh, governor of the Federal Reserve Board At the U.S.

As at most investment banks, its levers were pulled exclusively by a short list of managers who ran divisions like fixed income, equities, and prime brokerage, which handled trading and lending to Bear’s most important hedge fund clients. Managers in places like risk management and operations were considered less important to the firm’s core franchise and therefore largely excluded from important decisions. Tonight’s gathering, at which nearly all the power players were present, guaranteed a clash of opinions and egos. For months Bear had been struggling with a choppy stock market, plummeting home values, and an exodus of the lenders and clients that were its life-blood. The developments had created deep fissures within Bear’s sharp-elbowed ruling class. The trader who ran mortgages had nearly come to blows with the cochief of equities the prior fall over whether the fixed-income department, which included the mortgage unit, deserved bonuses after such a terrible year.

With a leverage, or debt-to-cash ratio, of 30 to 1—meaning that for every $1 it actually held in cash, Bear had borrowed $30 from other parties—the firm had one of the heaviest debt loads of any firm on the Street. That made it more vulnerable than other firms when repo lenders faced a crisis of confidence. To streamline the daily lending process, Bear operated financing desks in the fixed-income and equities units staffed by people whose job it was to “roll,” or renew, expiring loan agreements on a nightly, weekly, or monthly basis. Eyes turned now to Tim Greene, one of the two heads of Bear’s fixed-income financing desk. Greene, a West Point graduate with a soldier’s sense of loyalty, had been working at Bear for twenty-four years, rising through the ranks to help run the bond unit’s repo desk, which handled about $160 billion of funding at any given point—about half of Bear’s entire balance sheet.


Capital Ideas Evolving by Peter L. Bernstein

Albert Einstein, algorithmic trading, Andrei Shleifer, asset allocation, business cycle, buy and hold, buy low sell high, capital asset pricing model, commodity trading advisor, computerized trading, creative destruction, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, diversification, diversified portfolio, endowment effect, equity premium, Eugene Fama: efficient market hypothesis, financial innovation, fixed income, high net worth, hiring and firing, index fund, invisible hand, Isaac Newton, John Meriwether, John von Neumann, Joseph Schumpeter, Kenneth Arrow, London Interbank Offered Rate, Long Term Capital Management, loss aversion, Louis Bachelier, market bubble, mental accounting, money market fund, Myron Scholes, paper trading, passive investing, Paul Samuelson, price anchoring, price stability, random walk, Richard Thaler, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, Sharpe ratio, short selling, Silicon Valley, South Sea Bubble, statistical model, survivorship bias, systematic trading, technology bubble, The Wealth of Nations by Adam Smith, transaction costs, yield curve, Yogi Berra, zero-sum game

Hord explains that the Index Investor would still be guaranteed the return on the international index fund, and that guarantee would be collateralized by $200 million transferred to the Asset Trust from the foundation’s fixed-income assets. For safety’s sake, the fixed-income allocation would be converted from BGI’s active management to the BGI fixed-income index fund, but the fixed-income return would continue to accrue to the foundation. All earnings on all assets involved would be reinvested. Let us review what has happened. The Index Investor’s holding in the BGI international equity fund has been liquidated, with the proceeds transferred to the foundation’s outside active international equity manager. Meanwhile, the Index Investor continues to earn the return on the international index fund, at no cost and zero tracking error, plus the promised spread over that return to compensate it for contributing assets to the Trust. The foundation’s actively managed fixed-income portfolio has been converted into an index fund and is now held in the Trust as collateral against the Index Investor’s advance of its international equity assets.

But while these constraints may make the optimizer better behaved, they also create a new dilemma: Too many constraints dilute the advantages of using the optimizer in the first place. The problem of how optimizers misbehave first came to the attention of the quantitative analysts at Goldman Sachs in 1989, not long bern_c15.qxd 3/23/07 226 9:12 AM Page 226 THE PRACTITIONERS after Litterman had become head of fixed-income research. The head of fixed-income management in Goldman’s Tokyo office had asked Litterman to develop a model for building global fixed-income portfolios that would be appropriate for Japanese investors. The task soon expanded to building a global model for composing fixed-income portfolios for Goldman’s clients all over the world. Litterman was uncertain as to how should he begin this assignment, and decided to consult Black. Black was interested in the challenge, but it was not his habit to think of models in terms of the real world.

BGI would then liquidate the Trust’s holdings and turn over $308 million of that money to the Index Investor for reinvestment in the international equity index fund. This leaves a net profit of $44 million on the foundation’s account plus the performance on the fixed-income fund within the Trust. Thus, the alpha of $44 million was “ported” from the active international manager to the foundation’s fixed-income fund that collateralized the deal. The story is not necessarily destined to have such a happy ending. Suppose the returns were reversed, with the index fund earning 12 percent a year and the active manager stumbling behind at 9 percent. Now the foundation would have accumulated only $308 million, while the Index Investor would have accumulated a claim of $352 million. The foundation would have to liquidate $44 million from its fixed-income portfolio in order to make good on its guarantee to the Index Investor. There is still a portable alpha in the deal, but the alpha would be negative instead of positive.


pages: 345 words: 86,394

Frequently Asked Questions in Quantitative Finance by Paul Wilmott

Albert Einstein, asset allocation, beat the dealer, Black-Scholes formula, Brownian motion, butterfly effect, buy and hold, capital asset pricing model, collateralized debt obligation, Credit Default Swap, credit default swaps / collateralized debt obligations, delta neutral, discrete time, diversified portfolio, Edward Thorp, Emanuel Derman, Eugene Fama: efficient market hypothesis, fixed income, fudge factor, implied volatility, incomplete markets, interest rate derivative, interest rate swap, iterative process, lateral thinking, London Interbank Offered Rate, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, margin call, market bubble, martingale, Myron Scholes, Norbert Wiener, Paul Samuelson, quantitative trading / quantitative finance, random walk, regulatory arbitrage, risk/return, Sharpe ratio, statistical arbitrage, statistical model, stochastic process, stochastic volatility, transaction costs, urban planning, value at risk, volatility arbitrage, volatility smile, Wiener process, yield curve, zero-coupon bond

Jump diffusion Given the jump-diffusion modeldS = µS dt + σS dX + (J − 1)S dq, the equation for an option is E[·] is the expectation taken over the jump size. If the logarithm of J is Normally distributed with standard deviation σ′ then the price of a European non-path-dependent option can be written as where and and VBS is the Black-Scholes formula for the option value in the absence of jumps. Fixed Income In the following we use the continuously compounded interest convention. So that one dollar put in the bank at a constant rate of interest r would grow exponentially, ert. This is the convention used outside the fixed-income world. In the fixed-income world where interest is paid discretely, the convention is that money grows according to(1 + r′τ)n, where n is the number of interest payments, τ is the time interval between payments (here assumed constant) and r′ is the annualized interest rate. To convert from discrete to continuous use The yield to maturity (YTM) or internal rate of return (IRR) Suppose that we have a zero-coupon bond maturing at time T when it pays one dollar.

Example In the LMM the variables are a set of forward rates for traded, simple fixed-income instruments. The parameters are volatilities of these and correlations between them. From no arbitrage we can find the risk-neutral drift rates for these variables. The model is then used to price other instruments. Long Answer The history of interest-rate modelling begins with deterministic rates, and the ideas of yield to maturity, duration, etc. The assumption of determinism is not at all satisfactory for pricing derivatives however, because of Jensen’s Inequality. In 1976 Fischer Black introduced the idea of treating bonds as underlying assets so as to use the Black-Scholes equity option formulæ for fixed-income instruments. This is also not entirely satisfactory since there can be contradictions in this approach.

For that reason there have been developed other interest rate models that are internally consistent. In all of the spot rate models below we havedr = u(r,t)dt + w(r,t)dX as the real process for the spot interest rate. The risk-neutral process which governs the value of fixed-income instruments isdr = (u − λw)dt + w dX where λ is the market price of interest rate risk. In each case the stochastic differential equation we describe is for the risk-neutral spot rate process, not the real. The differential equation governing the value of non-path-dependent contracts is The value of fixed-income derivatives can also be interpreted as [Present value of cashflows], where the expectation is with respect to the risk-neutral process Vasicek In this model the risk-neutral process isdr = (a − br )dt + c dX, with a, b and c being constant.


pages: 192 words: 75,440

Getting a Job in Hedge Funds: An Inside Look at How Funds Hire by Adam Zoia, Aaron Finkel

backtesting, barriers to entry, collateralized debt obligation, commodity trading advisor, Credit Default Swap, credit default swaps / collateralized debt obligations, discounted cash flows, family office, fixed income, high net worth, interest rate derivative, interest rate swap, Long Term Capital Management, merger arbitrage, offshore financial centre, random walk, Renaissance Technologies, risk-adjusted returns, rolodex, short selling, side project, statistical arbitrage, stocks for the long run, systematic trading, unpaid internship, value at risk, yield curve, yield management

Positions are designed to generate profits from the fixed income security as well as the short sale of stock, while protecting principal from market moves. Fixed Income Arbitrage A fund that follows this strategy aims to profit from price anomalies between related interest rate securities. Most managers trade globally with a goal of generating steady returns with low volatility. This category includes interest rate swap arbitrage, U.S. and non-U.S. government bond arbitrage, forward yield curve arbitrage, and mortgage-backed securities (MBS) arbitrage. The mortgage-backed market is primarily U.S.-based, over-the-counter (OTC), and particularly complex. Note: Fixed income arbitrage is a generic description of a variety of strategies involving investments in fixed income instruments, and weighted in an attempt to eliminate or reduce exposure to changes in the yield curve.

Note: This is primarily an equity-based style. Fixed Income Strategies There are many different fixed income funds that invest in various types of debt instruments, including mortgage-backed securities (MBS), collateralized debt obligations (CDOs), collateralized loan obligations (CLOs), convertible bonds, high-yield bonds, municipal bonds, corporate bonds, and different types of global securities. There are diversified funds that may invest in a combination of these securities and also arbitrage funds that seek to profit by exploiting pricing inefficiencies between related fixed income securities while neutralizing exposure to interest rate risk. Convertible Bonds Convertible bond funds are primarily long only convertible bonds. By definition, convertible bonds are fixed-income securities with the added attraction of giving holders a stock option to buy shares of the underlying company.

c01.indd 5 1/10/08 11:00:55 AM 6 Getting a Job in Hedge Funds Table 1.3 Instruments and Styles COMMONLY USED INSTRUMENTS HEDGE FUND STYLES Public Equities Long/Short Quantitative Fixed Income Long Bias Event-Driven/Special Situations Currencies Short Only Value Commodities Arbitrage Trading Oriented Derivatives/Futures Market Neutral Global Macro Private Equity Industry Focus Multi-strategy Convertible Bonds Distressed Geographic Focus Arbitrage Strategies There are various types of arbitrage strategies, and all seek to exploit imbalances between different financial markets such as currencies, commodities, and debt. Some of the more popular hedge fund arbitrage strategies are convertible fixed income, risk, and statistical arbitrage. Convertible Arbitrage This strategy is identified by hedge investing in the convertible securities of a company.


pages: 537 words: 144,318

The Invisible Hands: Top Hedge Fund Traders on Bubbles, Crashes, and Real Money by Steven Drobny

Albert Einstein, Asian financial crisis, asset allocation, asset-backed security, backtesting, banking crisis, Bernie Madoff, Black Swan, Bretton Woods, BRICs, British Empire, business cycle, business process, buy and hold, capital asset pricing model, capital controls, central bank independence, collateralized debt obligation, commoditize, Commodity Super-Cycle, commodity trading advisor, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency peg, debt deflation, diversification, diversified portfolio, equity premium, family office, fiat currency, fixed income, follow your passion, full employment, George Santayana, Hyman Minsky, implied volatility, index fund, inflation targeting, interest rate swap, inventory management, invisible hand, Kickstarter, London Interbank Offered Rate, Long Term Capital Management, market bubble, market fundamentalism, market microstructure, moral hazard, Myron Scholes, North Sea oil, open economy, peak oil, pension reform, Ponzi scheme, prediction markets, price discovery process, price stability, private sector deleveraging, profit motive, purchasing power parity, quantitative easing, random walk, reserve currency, risk tolerance, risk-adjusted returns, risk/return, savings glut, selection bias, Sharpe ratio, short selling, sovereign wealth fund, special drawing rights, statistical arbitrage, stochastic volatility, stocks for the long run, stocks for the long term, survivorship bias, The Great Moderation, Thomas Bayes, time value of money, too big to fail, transaction costs, unbiased observer, value at risk, Vanguard fund, yield curve, zero-sum game

I started at the bottom, rolling currency positions and taking some small risk of my own. I honed my trading skills and eventually became desk manager. From there I moved into fixed income back in Minneapolis, where I again started at the bottom of the desk: rolling fixed income positions for the financial division (repo and reverse repo), concomitantly trading fixed income and currency exposures. I view these housekeeping trading roles—rolling currency positions, repo/reverse repo, stock borrow/lend, and futures rolls—as integral to the process of learning the pulse of any market. My next position took me to Australia, where I managed our branch office in Melbourne, a position that entailed overseeing portfolios in currency, fixed income, and equities markets, as well as responsibility for accounting functions. Eventually, I pitched management a business plan to start a proprietary risk-taking desk based on my profile and theme approach.

See European Central Bank Economic crash (2008) banks, problems foresight Economic cycle, driver (location) Economic entity, presence Economic leverage, accounting leverage (contrast) Economy, double dip (hypothesis) Efficient frontier leverage, relationship Efficient markets, disbelief Electorate-adjusted El-Erian, Mohamed Emerging markets bearish markets bubble collapse corporate bonds, usage decoupling equities, selection Employee pension scheme, capital allocation End of the Line, The (Lynn) Endowment Model flaws invalidation orientation portfolio resemblance Endowments cash level Commodity Hedger process decrease in-house trading staff, absence problems Energy, usage Equities bubble/overvaluation performance risk, commodity risk (contrast) risk premium, faith risky assets Equity assets, U.S. public/private pension ownership Equity bubble, conditions Equity-centric portfolio, endorsement (Swensen) Equity concentration risk, awareness Equity index futures, usage Equity-like instruments, usage Equity multiples (1980-2000) Equity-oriented portfolios, decrease Equity returns, Harvard/Yale endowments (contrast) Equity Trader, The adaptability call blow-ups, avoidance business entry CalPERS operation core positions trading, indices/options (usage) discipline, lessons environment differentiation focus fundamentals, understanding future adaptability hedge fund operation, worries outlook interview investor meetings lessons manager, investor base (impact) market environment identification momentum trades, options (usage) performance, randomness P&L, trading portfolio construction positioning, understanding private deals, execution profit-taking process real money fund management research team, usage risk framework transition rules, discovery socialism, concern sovereign wealth fund operation stockholder understanding stocks, shorting/ownership (contrast) taxes, hedge traders competition hiring criteria trades ideas, origination quality risk/reward, change trading accounts, problems decisions, policy makers (impact) disaster preplanning sharpness style, implementation worldview Euro, two-year Euro interest rates European Central Bank (ECB) inflation targeting European Currency Unit (ECU) basket European Exchange Rate (ERM) European Monetary Unit (EMU) European Union, breakage (potential) Excess demand, control Excess return, valuation Exchange rate valuation, P/E multiples (relationship) Exchange-traded funds (ETFs) allowance usage Export land model Extreme scenarios, protection (purchase) Faber, Mark Family office manager Fat-tail events Favorite Trade concept format, Plasticine Macro Trader disapproval Federal Reserve Funds, target rate (2008) independence, cessation Feedback, impact Ferguson, Niall Fiat currencies, impact Fiat money, cessation Filipino Diaspora Finance, diversification (impact) Financial bubble, risk Financial instruments, usage Financials, future Financial stocks (2007-2008) Financing problems Firm-level risk management Fiscal policy easing role, impact underestimation Fiscal stimulus China impact Fixed income trading, focus Fixed income volatility trade Flexibility, value (example) Fordham Law School, support Forecast combinations, improvement Forecasting model parameters, estimation Foreign currency diversification, usage Foreign Direct Investment (FDI) Forward fixed income Forward price, spot price (contrast) Forward-starting volatility Friedman, Milton Front contracts, physical commodities Fundamental investing/research, time frames (matching) Fundamentals, understanding Fund management, skill Fund performance, indicator Future benefit obligations, earnings Future correlations, usage FX forwards G3/G7 liquid rate, arbitrage opportunity (absence) G7 demand G7 economies, problems G10 policy General Theory of Employment, Interest, and Money, The (Keynes) German Schatz contracts Global adjustment period Global dollar carry trade Global economy, weakness Global equities decrease markets, decline Global fund management industry Global governments, financial system (backstopping) Globalization, meaning Global macro approach Global macro funds, factors Global macro hedge fund managers Global warming, carbon dioxide (impact) Gold (1979-1980) (1999) (2000-2009) (2004-2009) pension fund base currency safety Good leverage, classification Government bonds bull market (1985-2009) leverage, change LIBOR positions, leverage safety Government debt, funding Government default risk Government stimulus, payment Grantham, Jeremy Great Britain, ERM absence Great Depression spending, decrease taxes, increase Great Macro Experiment.

Bonds were selected from preapproved “legal lists” of securities, and it was common to have a limit for equities. In 1949, public and private pension assets in the United States were $15.7 billion. The asset mix was roughly half in government bonds, and half in other fixed income and insurance company fixed annuity investment products. There was minimal exposure to equities. Figure 1.2 Growth of US Public and Private Pension Fund Assets, 1950-2008 SOURCE: Federal Reserve Flow of Funds. Along Came Inflation By 1970, public and corporate pension fund assets in the United States reached $211.7 billion, the majority of which was concentrated in fixed income. Beginning with the 1973-1974 oil embargo, wave after wave of commodity price-induced inflation roiled fixed interest portfolios through the remainder of the decade. Nevertheless, assets continued to pour into pension funds because of strict commitments mandated on employers.


Stocks for the Long Run, 4th Edition: The Definitive Guide to Financial Market Returns & Long Term Investment Strategies by Jeremy J. Siegel

addicted to oil, asset allocation, backtesting, Black-Scholes formula, Bretton Woods, business cycle, buy and hold, buy low sell high, California gold rush, capital asset pricing model, cognitive dissonance, compound rate of return, correlation coefficient, Daniel Kahneman / Amos Tversky, diversification, diversified portfolio, dividend-yielding stocks, dogs of the Dow, equity premium, Eugene Fama: efficient market hypothesis, Everybody Ought to Be Rich, fixed income, German hyperinflation, implied volatility, index arbitrage, index fund, Isaac Newton, joint-stock company, Long Term Capital Management, loss aversion, market bubble, mental accounting, Myron Scholes, new economy, oil shock, passive investing, Paul Samuelson, popular capitalism, prediction markets, price anchoring, price stability, purchasing power parity, random walk, Richard Thaler, risk tolerance, risk/return, Robert Shiller, Robert Shiller, Ronald Reagan, shareholder value, short selling, South Sea Bubble, stocks for the long run, survivorship bias, technology bubble, The Great Moderation, The Wisdom of Crowds, transaction costs, tulip mania, Vanguard fund

CHAPTER 1 Stock and Bond Returns Since 1802 TABLE 15 1–2 Fixed-Income Returns, 1802 through December 2006 You have to go back more than 11⁄2 centuries to the period from 1831 through 1861 to find any 30-year period during which the return on either long- or short-term bonds exceeded that on equities. The dominance of stocks over fixed-income securities is overwhelming for investors with long horizons. THE FALL IN FIXED-INCOME RETURNS Although the returns on equities have fully compensated stock investors for the increased inflation since World War II, the returns on fixedincome securities have not. The change in the monetary standard from gold to paper had a far greater impact on the returns of fixed-income assets than on stocks. It is clear that the buyers of long-term bonds in the 1940s, 1950s, and early 1960s did not recognize the inflationary consequences of the change in monetary regime. How else can you explain 16 PART 1 The Verdict of History why investors voluntarily purchased 30-year bonds with 3 and 4 percent coupons ignoring a government policy that favored inflation?

For more information about this title, click here C O N T E N T S Foreword xv Preface xvii Acknowledgments xxi PART 1 THE VERDICT OF HISTORY Chapter 1 Stock and Bond Returns Since 1802 3 “Everybody Ought to Be Rich” 3 Financial Market Returns from 1802 5 The Long-Term Performance of Bonds 7 The End of the Gold Standard and Price Stability 9 Total Real Returns 11 Interpretation of Returns 12 Long-Term Returns 12 Short-Term Returns and Volatility 14 Real Returns on Fixed-Income Assets 14 The Fall in Fixed-Income Returns 15 The Equity Premium 16 Worldwide Equity and Bond Returns: Global Stocks for the Long Run 18 Conclusion: Stocks for the Long Run 20 Appendix 1: Stocks from 1802 to 1870 21 Appendix 2: Arithmetic and Geometric Returns 22 v vi Chapter 2 Risk, Return, and Portfolio Allocation: Why Stocks Are Less Risky Than Bonds in the Long Run 23 Measuring Risk and Return 23 Risk and Holding Period 24 Investor Returns from Market Peaks 27 Standard Measures of Risk 28 Varying Correlation between Stock and Bond Returns 30 Efficient Frontiers 32 Recommended Portfolio Allocations 34 Inflation-Indexed Bonds 35 Conclusion 36 Chapter 3 Stock Indexes: Proxies for the Market 37 Market Averages 37 The Dow Jones Averages 38 Computation of the Dow Index 39 Long-Term Trends in the Dow Jones 40 Beware the Use of Trend Lines to Predict Future Returns 41 Value-Weighted Indexes 42 Standard & Poor’s Index 42 Nasdaq Index 43 Other Stock Indexes: The Center for Research in Security Prices (CRSP) 45 Return Biases in Stock Indexes 46 Appendix: What Happened to the Original 12 Dow Industrials?

The long-term perspective radically changes one’s view of the risk of stocks. The shortterm fluctuations in the stock market, which loom so large to investors when they occur, are insignificant when compared to the upward movement of equity values over time. In contrast to the remarkable stability of stock returns, real returns on fixed-income assets have declined markedly over time. In the first and even second subperiods, the annual returns on bonds and bills, although less than those on equities, were significantly positive. But since 1926, and especially since World War II, fixed-income assets have returned little after inflation. INTERPRETATION OF RETURNS Long-Term Returns The annual returns on U.S. stocks over the past two centuries are summarized in Table 1-1.15 The shaded column represents the real after-inflation, compound annual rate of return on stocks.


pages: 517 words: 139,477

Stocks for the Long Run 5/E: the Definitive Guide to Financial Market Returns & Long-Term Investment Strategies by Jeremy Siegel

Asian financial crisis, asset allocation, backtesting, banking crisis, Black-Scholes formula, break the buck, Bretton Woods, business cycle, buy and hold, buy low sell high, California gold rush, capital asset pricing model, carried interest, central bank independence, cognitive dissonance, compound rate of return, computer age, computerized trading, corporate governance, correlation coefficient, Credit Default Swap, Daniel Kahneman / Amos Tversky, Deng Xiaoping, discounted cash flows, diversification, diversified portfolio, dividend-yielding stocks, dogs of the Dow, equity premium, Eugene Fama: efficient market hypothesis, eurozone crisis, Everybody Ought to Be Rich, Financial Instability Hypothesis, fixed income, Flash crash, forward guidance, fundamental attribution error, housing crisis, Hyman Minsky, implied volatility, income inequality, index arbitrage, index fund, indoor plumbing, inflation targeting, invention of the printing press, Isaac Newton, joint-stock company, London Interbank Offered Rate, Long Term Capital Management, loss aversion, market bubble, mental accounting, money market fund, mortgage debt, Myron Scholes, new economy, Northern Rock, oil shock, passive investing, Paul Samuelson, Peter Thiel, Ponzi scheme, prediction markets, price anchoring, price stability, purchasing power parity, quantitative easing, random walk, Richard Thaler, risk tolerance, risk/return, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Reagan, shareholder value, short selling, Silicon Valley, South Sea Bubble, sovereign wealth fund, stocks for the long run, survivorship bias, technology bubble, The Great Moderation, the payments system, The Wisdom of Crowds, transaction costs, tulip mania, Tyler Cowen: Great Stagnation, Vanguard fund

The Realities We Face The Age Wave Rising Life Expectancy Falling Retirement Age The Retirement Age Must Rise World Demographics and the Age Wave Fundamental Question Emerging Economies Can Fill the Gap Can Productivity Growth Keep Pace? Conclusion PART II THE VERDICT OF HISTORY Chapter 5 Stock and Bond Returns Since 1802 Financial Market Data from 1802 to the Present Total Asset Returns The Long-Term Performance of Bonds Gold, the Dollar, and Inflation Total Real Returns Real Returns on Fixed-Income Assets The Continuing Decline in Fixed-Income Returns The Equity Premium Worldwide Equity and Bond Returns Conclusion: Stocks for the Long Run Appendix 1: Stocks from 1802 to 1870 Chapter 6 Risk, Return, and Portfolio Allocation Why Stocks Are Less Risky Than Bonds in the Long Run Measuring Risk and Return Risk and Holding Period Standard Measures of Risk Varying Correlation Between Stock and Bond Returns Efficient Frontiers Conclusion Chapter 7 Stock Indexes Proxies for the Market Market Averages The Dow Jones Averages Computation of the Dow Index Long-Term Trends in the Dow Jones Industrial Average Beware the Use of Trendlines to Predict Future Returns Value-Weighted Indexes Standard & Poor’s Index Nasdaq Index Other Stock Indexes: The Center for Research in Security Prices Return Biases in Stock Indexes Appendix: What Happened to the Original 12 Dow Industrials?

Nevertheless, this great bull market carried stocks too high, and the valuation of the market reached record levels, which in turn led to the poor returns of the following decade. The subsequent bear market and financial crisis plunged stocks once again well below trend as real stock returns have fallen to a mere +0.3 percent in the 12 years following the bull market peak of 2000. REAL RETURNS ON FIXED-INCOME ASSETS As stable as the long-term real returns have been for equities, the same cannot be said of fixed-income assets. As Table 5-2 indicates, the real return on Treasury bills has dropped precipitously from 5.1 percent in the early part of the nineteenth century to a bare 0.6 percent since 1926, a return only slightly above inflation. TABLE 5-2 Real Returns on Bonds and Inflation 1802–2012 The real return on long-term bonds has shown a similar, but more moderate, decline.

The standard deviation of average returns falls nearly twice as fast for stocks as for fixed-income assets as the holding period increases. If asset returns follow a random walk, the standard deviation of each asset class will fall by the square root of the holding period. A random walk is a process whereby future returns are completely independent of past returns. The dashed bars in Figure 6-2 show the decline in risk predicted under the random walk assumption. But the historical data show that the random walk hypothesis cannot be maintained for equities. This occurs since the actual risk of average stock returns declines far faster than predicted by the random walk hypothesis because of the mean reversion of equity returns. The standard deviation of average returns for fixed-income assets, on the other hand, does not fall as fast as the random walk theory predicts.


pages: 1,202 words: 424,886

Stigum's Money Market, 4E by Marcia Stigum, Anthony Crescenzi

accounting loophole / creative accounting, Asian financial crisis, asset allocation, asset-backed security, bank run, banking crisis, banks create money, Black-Scholes formula, Brownian motion, business climate, buy and hold, capital controls, central bank independence, centralized clearinghouse, corporate governance, credit crunch, Credit Default Swap, currency manipulation / currency intervention, David Ricardo: comparative advantage, disintermediation, distributed generation, diversification, diversified portfolio, financial innovation, financial intermediation, fixed income, full employment, high net worth, implied volatility, income per capita, intangible asset, interest rate derivative, interest rate swap, large denomination, locking in a profit, London Interbank Offered Rate, margin call, market bubble, market clearing, market fundamentalism, money market fund, mortgage debt, Myron Scholes, offshore financial centre, paper trading, pension reform, Ponzi scheme, price mechanism, price stability, profit motive, Real Time Gross Settlement, reserve currency, risk tolerance, risk/return, seigniorage, shareholder value, short selling, technology bubble, the payments system, too big to fail, transaction costs, two-sided market, value at risk, volatility smile, yield curve, zero-coupon bond, zero-sum game

For example, in a rising interest-rate environment, Treasuries tend to be preferred over other securities, mostly because when rates rise, so do concerns about the economy, which can impair the ability of various types of borrowers (homeowners, corporations, etc.) to repay their debts. These concerns about the economy are hence manifested in the performance of “spread products,” or any fixed-income security that trades at a yield spread over Treasuries (all fixed-income securities). In recent years, banks have shown that they recognize the variations that can occur in the relative performance of fixed-income securities under different types of economic and interest-rate settings. Like most fixed-income investors, banks have shown an inclination to reach for as much yield as possible. This is evident in the current mix of securities held by the banking industry, which in June 2006 was skewed much more toward agencies and mortgage securities than toward Treasuries.19 Portfolio Management Active portfolio management by a bank—a willingness to make judgments about interest-rates trends and adjust maturities accordingly—can significantly increase the return earned by the bank on its portfolio.

THE PARAMETERS A liquidity portfolio is always managed within certain investment parameters that establish limits with respect to: (1) the types of instruments the portfolio may buy; (2) the percentage of the portfolio that may be invested in any one of these instruments (in T-bills the limit might be 100%, whereas in BAs or secondary loans, which are less liquid, it might be much lower); (3) the kind of exposure to names and credit risk the portfolio may assume (which banks’ paper and which issuers’ commercial paper it may buy and how much of each name it may buy, for example); (4) whether the portfolio may invest in international securities; (5) how far out on the maturity spectrum the portfolio may extend; (6) whether the portfolio may short securities or repo securities; (7) whether the portfolio may use futures, options, or other derivatives; and (8) whether the portfolio may take foreign-exchange risk or must always hedge. To assist in judging whether a portfolio is meeting these parameters, most large fixed-income portfolios compare their portfolios to that of a major fixed-income index such as the Lehman U.S. Aggregate Index. Indeed, Lehman claims that over 90% of U.S. investors use one or more of its fixed-income benchmarks to assist in analyzing their portfolios. Fixed-income managers use the indices largely to compare how their portfolios are constructed and to compare performance. The indices are an important resource for portfolio managers that help them in sticking to the parameters that are supposed to guide their investment decisions.

This book is a comprehensive guide to the money market—U.S. and Eurodollar. It is intended for people working in banks, in dealerships, and in other financial institutions; for people running liquidity portfolios; and for accountants, lawyers, students, and others who have an interest in the markets discussed. The book begins with an introduction to what goes on in fixed-income financial markets—financial intermediation and money creation—plus an introduction to how fixed-income securities work, including various concepts of yield, the meaning and importance of the yield curve and the messages embedded in it, and the concepts and calculation of duration and convexity. Next, the book analyzes the operations (domestic and Eurodollar) of money center banks, of money market dealers and brokers, of the Federal Reserve, and of managers of liquidity portfolios.


High-Frequency Trading by David Easley, Marcos López de Prado, Maureen O'Hara

algorithmic trading, asset allocation, backtesting, Brownian motion, capital asset pricing model, computer vision, continuous double auction, dark matter, discrete time, finite state, fixed income, Flash crash, High speed trading, index arbitrage, information asymmetry, interest rate swap, latency arbitrage, margin call, market design, market fragmentation, market fundamentalism, market microstructure, martingale, natural language processing, offshore financial centre, pattern recognition, price discovery process, price discrimination, price stability, quantitative trading / quantitative finance, random walk, Sharpe ratio, statistical arbitrage, statistical model, stochastic process, Tobin tax, transaction costs, two-sided market, yield curve

URL: http://www.sec.gov/ news/speech/2013/spch021913ebw.htm. 230 i i i i i i “Easley” — 2013/10/8 — 11:31 — page 231 — #251 i i Index (page numbers in italic type relate to tables or figures) A B algorithmic execution: and leaking of information, 159–83, 160, 162, 163, 165, 167, 168, 169, 171, 172, 174, 176–7, 178–9; see also AlphaMax; BadMax BadMax approach and data sample, 166–8, 168 and BadMax and gross and net alpha, 168–70 and clustering analysis, 170–4, 171, 172, 174 definition, 160–4 and GSET, 174–5, 176–7 and high alpha of large clusters, 170–4 and trading algorithms, 70–1 algorithms: generations of, 23–7 predatory, 8 tactical liquidity provision 10–11 trading: and algorithmic decision-making, 71–2 and algorithmic execution, 70–1 evolution of, 22–8 generations, 23–7; see also trading algorithms, evolution of and indicator zoology, 27–8 and transaction cost, 28–31 AlphaMax, 160–6 passim see also BadMax; information leakage alternative limit order book, 80–6 agent-based model, 83–5, 86 results and conclusion, 85 and spread/price–time priority, 82–3 BadMax 159–83 passim, 169, 178–9, 180–2 and data sample, 166–8 and gross and net alpha, 168–70 profitability grid, 180–2 see also algorithmic execution: and leaking information; AlphaMax; information leakage Black Wednesday, 8 C clustering analysis, and high alpha of large clusters, 170–4 CME, Nasdaq’s joint project with, xvi cointegration, 44, 53–9 Consolidated Audit Tape (CAT), 216 construction of trading signals, 31–8 and order book imbalance, 36–8 and timescales and weights, 31–3, 33 and trade sign autocorrelations, 34–6 cumulative distribution function, 130–1 D dark pools, smart order routing in, 115–22 E equity markets: execution strategies in, 21–41, 25, 29, 30, 33, 35, 37, 38, 40 and fair value and order protection, 38–41, 40 i i i i i i “Easley” — 2013/10/8 — 11:31 — page 232 — #252 i i HIGH-FREQUENCY TRADING and trading signals, construction of, 31–8; see also trading signals and types of client or market agent, 22 European Exchange Rate Mechanism (ERM), sterling joins, 8 execution shortfall, and information leakage, 164–6, 165; see also information leakage execution strategies: in equity markets, 21–41, 25, 29, 30, 33, 35, 37, 38, 40 and fair value and order protection, 38–41, 40 and trading signals, construction of, 31–8; see also trading signals in fixed-income markets, 43–62, 47, 48, 49, 50, 51, 52, 54, 55, 57, 58, 61 and cointegration, 44, 53–9 and information events, 44, 46–53 and pro rata matching, 44, 59–62 and fixed-income products, 44–6 experimental evaluation, 133–40 F fair value and order protection, 38–41, 40 fixed-income markets: execution strategies in, 43–62, 47, 48, 49, 50, 51, 52, 54, 55, 57, 58, 61 and cointegration, 44, 53–9 and information events, 44, 46–53 and pro rata matching, 44, 59–62 and short-term interest rates, 45–6 and Treasury futures, 46 fixed-income products, 44–6 and short-term interest rates, 45–6 and Treasury futures, 46, 47, 48, 51, 52, 55 see also fixed-income markets flash crash, 2, 77–8, 207, 209–10, 210, 218 see also market stress foreign-exchange markets: and the currency market, 65–73 trading algorithms, 69–72 and trading frequencies, 65–73, 72, 73 venues, 66–9 high-frequency trading in, 65–88, 66, 72, 73, 86 academic literature, 74–80 and alternative limit order book, 80–6; see also main entry Foresight Project, 215, 217, 224 futures markets: microstructural volatility in, 125–41, 133, 134, 136, 137, 138–9 experimental evaluation, 133–40 HDF5 file format, 127 maximum intermediate return, 131–2 parallelisation, 132–3 test data, 126–7 and volume-synchronised probability of informed trading, 128–31 G Goldman Sachs Electronic Trading (GSET), 159, 160, 161, 163, 166–80 passim, 167, 168, 169, 174–5 H HDF5 file format, 127 high-frequency trading (HFT): and “cheetah traders”, 1, 13 232 i i i i i i “Easley” — 2013/10/8 — 11:31 — page 233 — #253 i i INDEX and event-based time paradigm, 15 in FX markets 65–88, 66, 72, 73, 86; see also foreign-exchange markets, 74–80 and alternative limit order book, 80–6; see also main entry and the currency market, 65–73 and trading frequencies, 65–73, 72, 73 legislative changes enable, 2 machine learning for, 91–123, 100, 101, 103, 104, 107, 108–9, 111, 117, 121 and high-frequency data, 94–6 and optimised execution in dark pools via censored exploration, 93 and optimised trade execution via reinforcement learning, 92 and predicting price movement from order book state, 92–3 and price movement from order book state, predicting, 104–15 and reinforcement learning for optimised trade execution, 96–104 and smart order routing in dark pools, 115–22 in market stress, 76–80 central bank interventions, 79–80 flash crash (2010), 77–8 yen appreciation (2007), 77 yen appreciation (2011), 78–9 markets’ operation and dynamic interaction changed by, xv and matching engine, 3, 4 and more than speed, 7–12 new paradigm in, 2–4 paradigm of, insights into, 1–17, 7, 10–11, 14 regulatory challenge of, 207–9, 210, 212, 214 good and bad news concerning, 208–14 and greater surveillance and coordination, proposals for, 215–18 and market rules, proposals to change, 218–25 and proposals to curtail HFT, 225–8 solutions, 214–28 statistics to monitor, developing, 15 and time, meaning of, 5–7 and volatility, heightening of, 12 see also low-frequency trading I implementation shortfall: approach to, illustrated, 192–203 daily estimation, 195–9 intra-day estimation, 199–203 shortfall calculations, 193–5 discussed, 186–9 with transitory price effects, 185–206, 196, 197, 198, 199, 200, 202, 203 implementation details, 204–5 and observed and efficient prices and pricing errors, 189–92 indicator zoology, 27–8 information events, 44, 46–53 and event microscope, 50–3 information leakage: and algorithmic execution, 159–83, 176–7, 178–9 BadMax approach and data sample, 166–8, 168 233 i i i i i i “Easley” — 2013/10/8 — 11:31 — page 234 — #254 i i HIGH-FREQUENCY TRADING and BadMax and gross and net alpha, 168–70 and clustering analysis, 170–4, 171, 172, 174 and GSET, 174–5, 176–7 and high alpha of large clusters, 170–4 defining, 160–4 and execution shortfall, 164–6, 165 see also AlphaMax; BadMax L large clusters, high alpha of, 170–4 Large Hadron Collider, 125–41 latency arbitrage, 9 leakage of information: and algorithmic execution, 159–83, 176–7, 178–9 BadMax approach and data sample, 166–8, 168 and BadMax and gross and net alpha, 168–70 and clustering analysis, 170–4, 171, 172, 174 and GSET, 174–5, 176–7 and high alpha of large clusters, 170–4 defining, 160–4 and execution shortfall, 164–6, 165 see also AlphaMax; BadMax liquidity squeezers, 9 liquidity and toxicity contagion, 143–56, 144, 145, 147, 148, 151, 153, 154 empirical analysis, 151–5 order-flow toxicity contagion model, 146–51 low-frequency trading: choices needed for survival of, 15 and event-based time paradigm, 15 joining the herd, 15 and monitoring of HFT activity, 15 and order-flow toxicity, monitoring, 16 and seasonal effects, avoiding, 16 and smart brokers, 16 see also high-frequency trading M machine learning: for high-frequency trading (HFT) and market microstructure, 91–123, 100, 101, 103, 104, 107, 108–9, 111, 117, 121 and high-frequency data, 94–6 and optimised execution in dark pools via censored exploration, 93 and optimised trade execution via reinforcement learning, 92 and predicting price movement from order book state, 92–3 and price movement from order book state, predicting, 104–15 and reinforcement learning for optimised trade execution, 96–104 and smart order routing in dark pools, 115–22 Market Information Data Analytics System (MIDAS), 215–16 market microstructure: machine learning for, 91–123, 100, 101, 103, 104, 107, 108–9, 111, 117, 121 and high-frequency data, 94–6 and optimised execution in dark pools via censored exploration, 93 and optimised trade execution via reinforcement learning, 92 234 i i i i i i “Easley” — 2013/10/8 — 11:31 — page 235 — #255 i i INDEX and predicting price movement from order book state, 92–3 and price movement from order book state, predicting, 104–15 and reinforcement learning for optimised trade execution, 96–104 and smart order routing in dark pools, 115–22 market stress: and central bank interventions, 79–80 and flash crash (2010), 77–8; see also flash crash and yen appreciation (2007), 77 and yen appreciation (2011), 78–9 Markets in Financial Instruments Directive (MiFID), 2, 21, 143, 216 microstructural volatility: in futures markets, 125–41, 133, 134, 136, 137, 138–9 experimental evaluation, 133–40 HDF5 file format, 127 maximum intermediate return, 131–2 parallelisation, 132–3 test data, 126–7 and volume-synchronised probability of informed trading, 128–31 MIDAS, see Market Information Data Analytics System N Nasdaq, CME’s joint project with, xvi O optimised trade execution, reinforcement learning for, 96–104 order book imbalance, 36–8 order-flow toxicity contagion model, 146–51 see also liquidity and toxicity contagion order protection and fair value, 38–41, 40 P pack hunters, 9 parallelisation, 132–3 price movement from order book state, predicting, 104–15 pro rata matching, 44, 59–62 probability of informed trading (PIN), 7 Project Hiberni, xvi Q quote danglers, 9 quote stuffers, 9 R regulation and high-frequency markets, 81, 207–9, 210, 212, 214 good and bad news concerning, 208–14 solutions, 214–28 and greater surveillance and coordination, proposals for, 215–18 and market rules, proposals to change, 218–25 and proposals to curtail HFT, 225–8 Regulation National Market System (Reg NMS), 2, 21, 143, 219 Regulation SCI, 216 reinforcement learning for optimised trade execution, 96–104 Rothschild, Nathan Mayer, 1 S smart order routing in dark pools, 115–22 spread/price–time priority, 82–3 235 i i i i i i “Easley” — 2013/10/8 — 11:31 — page 236 — #256 i i HIGH-FREQUENCY TRADING T time, meaning of, and high-frequency trading, 5–7, 7 Tobin tax, 17, 81, 87 Tradeworx, 215 trading algorithms, 69–72 and algorithmic decision-making, 71–2 and algorithmic execution, 70–1 evolution of, 22–8 generations, 23–7 and indicator zoology, 27–8 see also algorithms trading frequencies, in currency market, 65–73, 72, 73; see also foreign-exchange markets trading signals: construction of, 31–8 and order book imbalance, 36–8 and timescales and weights, 31–3, 33 and trade sign autocorrelations, 34–6 transaction cost, and algorithms, 28–31 transitory price effects: approach to, illustrated, 192–203 daily estimation, 195–9 implementation shortfall calculations, 193–5 intra-day estimation, 199–203 and information shortfall, 185–206, 196, 197, 198, 199, 200, 202, 203 discussed, 186–9 implementation details, 204–5 and observed and efficient prices and pricing errors, 189–92 Treasury futures, 46, 47, 48, 51, 52, 55 V volume clock, 1–17, 7 and time, meaning of, 5–7 volume-synchronised probability of informed trading, 128–31 bars, 128 buckets, 129–30 cumulative distribution function, 130–1 volume classification, 128–9 W Walter, Elisse, 216 Waterloo, Battle of, 1 Y yen appreciation: 2007, 77 2011, 78–9 see also market stress 236 i i i i

This change in matching algorithm has dramatic effects on the dynamics of the order book and optimal submission strategies. FIXED INCOME PRODUCTS The fixed-income universe is large and varied, from corporate bonds to municipal debt, mortgage-backed products and sovereign debt instruments, and includes various derived products such as swaps. Some of these products are traded only by dealers, and for some of them there is not even a central record of transactions. We shall focus on the subset of fixed-income products that are denoted “interest rate products”, that is, products for which default 44 i i i i i i “Easley” — 2013/10/8 — 11:31 — page 45 — #65 i i EXECUTION STRATEGIES IN FIXED INCOME MARKETS risk is negligible and market risk only comes from changes in the underlying interest rate. Such products are usually, though not always, sovereign debt of countries that have the ability to print the currency in which their debts are denominated.

As a consequence, quant researchers in equity markets have focused intensively on the details of the execution process. By contrast, fixed-income products are inherently complex, and quantitatively minded researchers in this area have focused on such aspects as yield curve modelling and day counts. Asset managers have not traditionally focused on measuring or managing execution costs, and have few effective tools to do so. However, the Securities Industry and Financial Markets Association (SIFMA) noted that “It is clear that the duty to seek best execution imposed on an asset manager is the same regardless of whether the manager is undertaking equity or fixed-income transactions” (SIFMAAsset Management Group 2008). 43 i i i i i i “Easley” — 2013/10/8 — 11:31 — page 44 — #64 i i HIGH-FREQUENCY TRADING This chapter discusses some details of the fixed-income markets that present special challenges for best execution in general and automated trading in particular.


pages: 1,073 words: 302,361

Money and Power: How Goldman Sachs Came to Rule the World by William D. Cohan

asset-backed security, Bernie Madoff, business cycle, buttonwood tree, buy and hold, collateralized debt obligation, corporate governance, corporate raider, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, diversified portfolio, fear of failure, financial innovation, fixed income, Ford paid five dollars a day, Goldman Sachs: Vampire Squid, Gordon Gekko, high net worth, hiring and firing, hive mind, Hyman Minsky, interest rate swap, John Meriwether, Kenneth Arrow, London Interbank Offered Rate, Long Term Capital Management, margin call, market bubble, mega-rich, merger arbitrage, moral hazard, mortgage debt, Myron Scholes, paper trading, passive investing, Paul Samuelson, Ponzi scheme, price stability, profit maximization, risk tolerance, Ronald Reagan, Saturday Night Live, South Sea Bubble, time value of money, too big to fail, traveling salesman, value at risk, yield curve, Yogi Berra, zero-sum game

It would have been a very difficult time if we had not sold the company.” Then there was the internecine warfare between Goldman and J. Aron about who should run the firm’s fixed-income business. “The three senior people from J. Aron got into a disagreement with the people at Goldman’s fixed-income group about whether J. Aron should have its own fixed-income department or they should use the Goldman Sachs fixed-income department, which is what I thought they should do,” Rubin explained. “I didn’t really want two competing fixed-income departments. It would be chaotic. But it actually was a long dispute, with Weinberg and Whitehead having different views, which is what made it complicated. Ultimately, we decided to have one fixed-income department. In any event, the three guys running J. Aron left.” Within a year of closing the acquisition, both Coyne and his partner Marvin Schur, who had been given the seat on Goldman’s Management Committee, had left Goldman, complaining of chest pains and other ailments.

.… Unexpected losses can develop rapidly and be huge.” Understandably, the losses in the fixed-income group led to some serious griping around the firm, especially when the firm lost another $200 million in fixed-income trading in February 1986. “They really got clobbered,” Friedman explained. “They didn’t have sufficient integration with research. And the internal morale was such that when you’d have monthly partners meetings, investment bankers would be saying to traders as they came off the elevator to go into the meeting, ‘Well how much money did you guys lose this month?’ That’s not a great morale thing.” Friedman and Rubin set about changing the gestalt of the fixed-income group by taking a most un-Goldman-like step: they hired a group of senior traders from Salomon Brothers—the fixed-income leader—to perform an extreme makeover. First, Goldman hired Thomas Pura, thirty-two, who chose to go to Harvard instead of signing up with the Kansas City Royals after high school.

Aside from why Friedman had seemingly botched his departure, the other lingering question that remained among many of the Goldman partners was how Corzine could have emerged as the firm’s leader when he was leading the very division—fixed-income—that had lost hundreds of millions of dollars in 1994. “He’s the only one who understood how to get out of it,” explained a fixed-income trader. “You have to have someone who knew how to get out of it.” Paulson tried to explain how this could have happened. “Fixed-income trading had grown to be a big part of the firm and its profits,” he said, “so effectively there wasn’t a choice. There had to be someone from the fixed-income side overseeing that business because that’s where the problems were.” Added another partner, about Corzine, “He is charming. He’s got a really nice style. He comes in an attractive package, so although he has got a huge ego and huge ambition—which far exceeds his ability in both those things—he comes across in a laid-back, low-key, disarming style.


pages: 457 words: 143,967

The Bank That Lived a Little: Barclays in the Age of the Very Free Market by Philip Augar

activist fund / activist shareholder / activist investor, Asian financial crisis, asset-backed security, bank run, banking crisis, Big bang: deregulation of the City of London, Bonfire of the Vanities, bonus culture, break the buck, call centre, collateralized debt obligation, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, family office, financial deregulation, financial innovation, fixed income, high net worth, hiring and firing, index card, index fund, interest rate derivative, light touch regulation, loadsamoney, Long Term Capital Management, Martin Wolf, money market fund, moral hazard, Nick Leeson, Northern Rock, offshore financial centre, old-boy network, out of africa, prediction markets, quantitative easing, Ronald Reagan, shareholder value, short selling, Sloane Ranger, Social Responsibility of Business Is to Increase Its Profits, sovereign wealth fund, too big to fail, wikimedia commons, yield curve

He had managed to get a meeting with Taylor the previous December and used it to float an idea. Wall Street’s fixed income departments – those buying and selling parcels of debt issued by companies and governments, also known as bond trading – were booming in 1995 but BZW’s were not, and Bycroft had noticed. ‘Are you convinced,’ he had asked Taylor, ‘that the existing management team in fixed income is up to the job and if not can I help out?’ Taylor had seen for himself, when American investment banks such as Goldman Sachs, J. P. Morgan and Morgan Stanley pitched business propositions to him, that the top US firms had a greater depth and quality of management than he saw at BZW. The current head of fixed income, Sam Marrone, a former US Marine who had served in Vietnam prior to working on Wall Street, was no slouch.

But was he, Taylor pondered, one of the really top people that could transform the business? He thanked Bycroft for the idea, promising to think about it, and a few days later attended Band’s away-day in Essex. After reflecting over the Christmas break, Taylor called Bycroft: ‘There is no retainer on this and no formal mandate. It is no win, no fee. But you can have the usual terms if you find us a new head of fixed income.’ Bycroft did not like fishing trips but the usual terms were a third of the first year’s compensation. For a global fixed income head, this could be worth half a million dollars and was too good to miss. There were only three or four people in the world capable of doing the job to the level Taylor had in mind and fewer still would countenance moving to London to a firm with a retail banking culture. Bycroft knew from the outset that Diamond was his man. A CAREER AT A CROSSROADS Diamond’s career had blossomed since he first travelled to Wall Street on the downtown train back in 1979.

He said he would want to replace nearly everyone and that the money was not important to him, what mattered was the opportunity. As he flew home, Diamond mulled over what he had heard. He felt that Barclays was a great bank that needed a capital markets arm if it was to remain great. It had a famous brand name and a strong credit rating, but the merchant bank’s fixed income model was that of a pre-Big Bang broker dealer making no money outside the UK and focused on old products. He believed that a modern European investment bank should be global and integrated, whereas BZW was domestic and fragmented. Would Taylor give him the freedom to redesign BZW’s fixed income division along modern lines? It was worth a try. After discussing with Jennifer whether the time was right to move their family to London again, in May 1996 he called Taylor: ‘I’ll come.’ It was a turning point in Barclays’ history. ‘IT’S HOW THEY DO THINGS HERE’ Diamond spent the Fourth of July holiday with his family on the island of Nantucket off the New England coast, waved them goodbye as he boarded the Cape Air shuttle to Boston and then took an overnight flight to London, landing in the morning of Sunday 7 July.


pages: 368 words: 145,841

Financial Independence by John J. Vento

Affordable Care Act / Obamacare, Albert Einstein, asset allocation, diversification, diversified portfolio, estate planning, financial independence, fixed income, high net worth, Home mortgage interest deduction, money market fund, mortgage debt, mortgage tax deduction, oil shock, Own Your Own Home, passive income, risk tolerance, the rule of 72, time value of money, transaction costs, young professional, zero day

c09.indd 237 26/02/13 2:51 PM 238 Financial Independence (Getting to Point X ) Exhibit 9.4 Seven Sample Asset Allocation Models (1 = Most risk-adverse investor; 7 = Most aggressive investor) 1 Conservative Bond Income 100% Fixed Income 15% Fixed Income: High Yield 50% Fixed Income: Short Term and Money Market 35% Fixed Income: Investment Grade 2 Conservative Income 80% Fixed Income & 20% Equity 2% Equity: International 2% Equity: Mid Cap 16% Equity: Large Cap 30% Fixed Income: Short Term and Money Market 20% Fixed Income: High Yield 30% Fixed Income: Investment Grade 3 Income 70% Fixed Income & 30% Equity 2% Equity: Small Cap 3% Equity: International 4% Equity: Mid Cap 20% Fixed Income: Short Term and Money Market 21% Equity: Large Cap 30% Fixed Income: Investment Grade 20% Fixed Income: High Yield c09.indd 238 26/02/13 2:51 PM Managing Your Investments 239 4 Conservative Growth 55% Fixed Income + 43% Equity + 2% Commodities + 2% Real Estate 2% Commodities 4% Equity: International 2% Real Estate 15% Fixed Income: Short Term and Money Market 3% Equity: Small Cap 5% Equity: Mid Cap 25% Fixed Income: Investment Grade 29% Equity: Large Cap 15% Fixed Income: High Yield 5 Growth 40% Fixed Income + 52% Equity + 4% Commodities + 4% Real Estate 7% Equity: International 4% Commodities 4% Real Estate 4% Equity: Small Cap 2% Fixed Income: Short Term and Money Market 25% Fixed Income: Investment Grade 13% Fixed Income: High Yield 35% Equity: Large Cap 6% Equity: Mid Cap (Continued ) c09.indd 239 26/02/13 2:51 PM 240 Financial Independence (Getting to Point X ) Exhibit 9.4 (Continued ) 6 Maximum Growth 20% Fixed Income + 70% Equity + 5% Commodities + 5% Real Estate 2% Fixed Income: Short Term and Money Market 5% Real Estate 5% Commodities 13% Fixed Income: Investment Grade 10% Equity: International 5% Fixed Income: High Yield 6% Equity: Small Cap 8% Equity: Mid Cap 46% Equity: Large Cap 7 Maximum Growth No Fixed Income 90% Equity + 5% Commodities + 5% Real Estate 5% Real Estate 5% Commodities 15% Equity: International 58% Equity: Large Cap 7% Equity: Small Cap 10% Equity: Mid Cap Depending on your risk tolerance and time horizon, you can select anywhere from model 1 to model 7; for example: • If you will need money in the near future, you should consider a model that involves less risk, such as model 1, 2, or 3. • If you are saving for retirement and have 10 or more years until you will need access to these funds, you may be able to take on more risk and would like to increase your potential for growth.

c09.indd 237 26/02/13 2:51 PM 238 Financial Independence (Getting to Point X ) Exhibit 9.4 Seven Sample Asset Allocation Models (1 = Most risk-adverse investor; 7 = Most aggressive investor) 1 Conservative Bond Income 100% Fixed Income 15% Fixed Income: High Yield 50% Fixed Income: Short Term and Money Market 35% Fixed Income: Investment Grade 2 Conservative Income 80% Fixed Income & 20% Equity 2% Equity: International 2% Equity: Mid Cap 16% Equity: Large Cap 30% Fixed Income: Short Term and Money Market 20% Fixed Income: High Yield 30% Fixed Income: Investment Grade 3 Income 70% Fixed Income & 30% Equity 2% Equity: Small Cap 3% Equity: International 4% Equity: Mid Cap 20% Fixed Income: Short Term and Money Market 21% Equity: Large Cap 30% Fixed Income: Investment Grade 20% Fixed Income: High Yield c09.indd 238 26/02/13 2:51 PM Managing Your Investments 239 4 Conservative Growth 55% Fixed Income + 43% Equity + 2% Commodities + 2% Real Estate 2% Commodities 4% Equity: International 2% Real Estate 15% Fixed Income: Short Term and Money Market 3% Equity: Small Cap 5% Equity: Mid Cap 25% Fixed Income: Investment Grade 29% Equity: Large Cap 15% Fixed Income: High Yield 5 Growth 40% Fixed Income + 52% Equity + 4% Commodities + 4% Real Estate 7% Equity: International 4% Commodities 4% Real Estate 4% Equity: Small Cap 2% Fixed Income: Short Term and Money Market 25% Fixed Income: Investment Grade 13% Fixed Income: High Yield 35% Equity: Large Cap 6% Equity: Mid Cap (Continued ) c09.indd 239 26/02/13 2:51 PM 240 Financial Independence (Getting to Point X ) Exhibit 9.4 (Continued ) 6 Maximum Growth 20% Fixed Income + 70% Equity + 5% Commodities + 5% Real Estate 2% Fixed Income: Short Term and Money Market 5% Real Estate 5% Commodities 13% Fixed Income: Investment Grade 10% Equity: International 5% Fixed Income: High Yield 6% Equity: Small Cap 8% Equity: Mid Cap 46% Equity: Large Cap 7 Maximum Growth No Fixed Income 90% Equity + 5% Commodities + 5% Real Estate 5% Real Estate 5% Commodities 15% Equity: International 58% Equity: Large Cap 7% Equity: Small Cap 10% Equity: Mid Cap Depending on your risk tolerance and time horizon, you can select anywhere from model 1 to model 7; for example: • If you will need money in the near future, you should consider a model that involves less risk, such as model 1, 2, or 3. • If you are saving for retirement and have 10 or more years until you will need access to these funds, you may be able to take on more risk and would like to increase your potential for growth.

Here, we start with the sample investment model 1, conservative bond income, with 15 percent allocated to fixed high-yield bonds, 35 percent allocated to fixedincome investment-grade bonds, and 50 percent to fixed-income short-term and money-market. After year 1, the initial asset allocation percentages have changed because of the performance of each asset class. In order to rebalance and put your model back to its original allocation, you would be required to purchase $1,875 of fixed-income short-term bond mutual funds and money-market and you would have to sell $788 of fixed-income investment-grade bond mutual funds and $1,088 of fixed-income high-yield bond mutual funds. This would take you back to your original percentage allocation. c09.indd 241 26/02/13 2:51 PM c09.indd 242 Exhibit 9.5 Investment Rebalancing Sample Investment Model 1 — Conservative Bond Income Market Value of Portfolio Fixed Income High Yield Total Initial Investment $100,000 % Change Year 1 Change During Year 1 Year-1 Before Rebalance 242 REBALANCE - Year 1 Year-1 After Rebalance Year-2 Before Rebalance REBALANCE - Year 2 Year-2 After Rebalance Year-3 Before Rebalance REBALANCE - Year 3 Year-3 After Rebalance Fixed Income Short Term and Money Market $15,000 $35,000 $50,000 10% 5% –1% $2,750 $1,500 $1,750 $(500) $16,500 $36,750 $49,500 $– $(1,088) $(788) $1,875 $102,750 $15,413 $35,963 $51,375 4% 6% 0% $2,774 $617 $2,158 $– $105,524 $16,029 $38,120 $51,375 $– $(200) $(1,187) $1,387 $105,524 $15,829 $36,933 $52,762 2% 3% 5% $4,063 $317 $1,108 $2,638 $109,587 $16,145 $38,041 $55,400 $– $293 $314 $(607) $109,587 $16,438 $38,355 $54,793 % Change Year 3 Change During Year 3 Fixed Income Investment Grade $102,750 % Change Year 2 Change During Year 2 % of Portfolio Total Fixed Income High Yield Fixed Income Investment Grade Fixed Income Short Term and Money Market 100.00% 15.00% 35.00% 50.00% 100.00% 16.06% 35.77% 48.18% 100.00% 15.00% 35.00% 50.00% 100.00% 15.19% 36.12% 48.69% 100.00% 15.00% 35.00% 50.00% 100.00% 14.73% 34.71% 50.55% 100.00% 15.00% 35.00% 50.00% 26/02/13 2:51 PM Managing Your Investments 243 In the example provided, rebalancing is being done once a year, always taking you back to your original asset-allocation model investment percentages.


pages: 1,088 words: 228,743

Expected Returns: An Investor's Guide to Harvesting Market Rewards by Antti Ilmanen

Andrei Shleifer, asset allocation, asset-backed security, availability heuristic, backtesting, balance sheet recession, bank run, banking crisis, barriers to entry, Bernie Madoff, Black Swan, Bretton Woods, business cycle, buy and hold, buy low sell high, capital asset pricing model, capital controls, Carmen Reinhart, central bank independence, collateralized debt obligation, commoditize, commodity trading advisor, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, debt deflation, deglobalization, delta neutral, demand response, discounted cash flows, disintermediation, diversification, diversified portfolio, dividend-yielding stocks, equity premium, Eugene Fama: efficient market hypothesis, fiat currency, financial deregulation, financial innovation, financial intermediation, fixed income, Flash crash, framing effect, frictionless, frictionless market, G4S, George Akerlof, global reserve currency, Google Earth, high net worth, hindsight bias, Hyman Minsky, implied volatility, income inequality, incomplete markets, index fund, inflation targeting, information asymmetry, interest rate swap, invisible hand, Kenneth Rogoff, laissez-faire capitalism, law of one price, London Interbank Offered Rate, Long Term Capital Management, loss aversion, margin call, market bubble, market clearing, market friction, market fundamentalism, market microstructure, mental accounting, merger arbitrage, mittelstand, moral hazard, Myron Scholes, negative equity, New Journalism, oil shock, p-value, passive investing, Paul Samuelson, performance metric, Ponzi scheme, prediction markets, price anchoring, price stability, principal–agent problem, private sector deleveraging, purchasing power parity, quantitative easing, quantitative trading / quantitative finance, random walk, reserve currency, Richard Thaler, risk tolerance, risk-adjusted returns, risk/return, riskless arbitrage, Robert Shiller, Robert Shiller, savings glut, selection bias, Sharpe ratio, short selling, sovereign wealth fund, statistical arbitrage, statistical model, stochastic volatility, stocks for the long run, survivorship bias, systematic trading, The Great Moderation, The Myth of the Rational Market, too big to fail, transaction costs, tulip mania, value at risk, volatility arbitrage, volatility smile, working-age population, Y2K, yield curve, zero-coupon bond, zero-sum game

Ilmanen, Antti (1996), “Market rate expectations and forward rates,” Journal of Fixed Income 6(2), 8–22 (originally published as part of a Salomon Brothers research paper series titled “Understanding the Yield Curve”). Ilmanen, Antti (1997), “Forecasting U.S. bond returns,” Journal of Fixed Income 7(1), 22–37 (originally published as part of a Salomon Brothers research paper series titled “Understanding the Yield Curve”). Ilmanen, Antti (2003a), “Expected returns on stocks and bonds,” Journal of Portfolio Management 29(2), 7–27. Ilmanen, Antti (2003b), “Stock–bond correlations,” Journal of Fixed Income 13(2), 55–66. Ilmanen, Antti; and Rory Byrne (2003), “Pronounced momentum patterns ahead of major events,” Journal of Fixed Income 12(4), 73-80. Ilmanen, Antti; Rory Byrne; Heinz Gunasekera; and Robert Minikin (2003), “Which risks have been best rewarded?”

Several main findings are familiar to most readers:• Stock markets have outperformed fixed income markets during the past century in all countries studied. The compound average real return for global equities between 1900 and 2009 is 5.4%, which is 3.7% (4.4%) higher than that of long-term government bonds (short-dated Treasury bills). Stocks’ outperformance over bonds is 0.5% to 0.8% higher for the U.S. than globally and was even more pronounced before the negative returns in 2000s. The experience of the current investor generation has buried the myth that stocks always beat bonds over 20-year or 30-year horizons. (This myth was never true. Many exceptions to it occurred outside the U.S. in the 20th century and inside the U.S. during the 19th century.) • Among fixed income markets, long-term bonds have outperformed short-dated bonds by 0.5% to 1% and credit-risky corporate bonds have outperformed comparable government bonds by 0.3% to 1% (low end for investment-grade bonds, high end for high-yield bonds).

Distinctions are even sharper if we subtract the common riskless return from all series and plot cumulative excess returns (cumulative outperformance over cash, here one-month deposit) (as in Figure 2.6). Developed market equities enjoyed persistent rallies in 1993–2000 and 2003–2007 but lost about half of their value in 2000–2003 and again in 2008. Partly due to the Japan drag, the asset class ended up underperforming emerging markets, fixed income, and real estate. Emerging market equities gave investors a characteristically bumpy ride but delivered the highest returns. Fixed income returns were most stable, while real estate (in the U.S.) was the best-performing asset class between the mid-1990s and 2007 but then busted. 2.3 FORWARD-LOOKING RETURN INDICATORS All historical return data may be beside the point if expected returns vary over time. One key theme in this book is that time-varying expected returns can make historical average returns highly misleading.


pages: 526 words: 158,913

Crash of the Titans: Greed, Hubris, the Fall of Merrill Lynch, and the Near-Collapse of Bank of America by Greg Farrell

Airbus A320, Apple's 1984 Super Bowl advert, bank run, banking crisis, bonus culture, call centre, Captain Sullenberger Hudson, collapse of Lehman Brothers, collateralized debt obligation, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, financial innovation, fixed income, glass ceiling, high net worth, Long Term Capital Management, mass affluent, Mexican peso crisis / tequila crisis, Nelson Mandela, plutocrats, Plutocrats, Ronald Reagan, six sigma, sovereign wealth fund, technology bubble, too big to fail, US Airways Flight 1549, yield curve

Osman Semerci, a rising star at Merrill Lynch, would make this presentation and walk the board of directors through Merrill Lynch’s fixed-income exposures. Just nine months earlier, O’Neal had encouraged the selection of Semerci, a thirty-eight-year-old native of Turkey, to be head of Merrill Lynch’s fixed-income, commodities, and currencies business, an area known on Wall Street as “FICC.” The term “fixed income” had grown more important on Wall Street over the previous decade because of the proliferation of products that, like bonds, provided a steady stream of payments to the owner. When he was stationed in Tokyo and then in London, Semerci had established himself as a master in the art of selling fixed-income products to other banks and investors. Nestled comfortably in a dining room at the Nassau Inn, the directors listened closely as Semerci outlined the successes he had engineered in less than one full year on the job: record revenues in FICC for 2006, followed by record revenues in the first quarter of 2007.

As a manager, he walked around the trading floor with a notebook, and would ostentatiously write something down in it when someone disagreed with him over a trade or another matter, implying that the incident would be remembered. In 2003, Dow Kim, a forty-year-old Korean, had been put in charge of all sales and trading operations. But by 2006, the fixed-income division was generating so much revenue every quarter (much of which came from Semerci, who was based in London), that Stan O’Neal felt the unit should have a full-time manager for the position. Kim had come under increasing pressure from O’Neal to boost Merrill’s FICC revenues up to the levels of Goldman Sachs, the industry leader in the category. Kim’s first choice for the job was an internal candidate, Jeff Kronthal, one of the top fixed-income people on Wall Street, who had a deep understanding of risk. But neither O’Neal nor Fakahany was enamored of the fifty-one-year-old Kronthal, who had recently become cautious about trades involving the real estate market.

The ouster of two highly regarded fixtures of the trading floor—on the same day that several board members were taking a tour of the trading desks—made for unusual theater. When Semerci arrived a few days later and was introduced to everyone by Dow Kim as the new FICC leader, fixed-income traders gathered on the seventh floor to take the measure of the new boss. Semerci made a few introductory remarks, talking about what he had been doing in Europe, then addressed the topic at hand: “I think the U.S. is very important,” he said. “I don’t know much about U.S. fixed income, but I’m excited to learn.” Most of the veteran traders, who had relied on the decades of expertise that Kronthal and his crew had brought to the game, listened in disbelief. Afterward, Dow Kim went around the room asking individual traders what they thought of the new guy, hoping for an enthusiastic response.


pages: 363 words: 28,546

Portfolio Design: A Modern Approach to Asset Allocation by R. Marston

asset allocation, Bretton Woods, business cycle, capital asset pricing model, capital controls, carried interest, commodity trading advisor, correlation coefficient, diversification, diversified portfolio, equity premium, Eugene Fama: efficient market hypothesis, family office, financial innovation, fixed income, German hyperinflation, high net worth, hiring and firing, housing crisis, income per capita, index fund, inventory management, Long Term Capital Management, mortgage debt, passive investing, purchasing power parity, risk-adjusted returns, Robert Shiller, Robert Shiller, Ronald Reagan, Sharpe ratio, Silicon Valley, stocks for the long run, superstar cities, survivorship bias, transaction costs, Vanguard fund

By the 1990s, interest in emerging stock markets also increased. Chapters 5 and 6 will examine these investments and will show how they help to diversify U.S. portfolios. Fixed income investments have evolved even more than stock investments. Forty years ago, Treasury and corporate bonds were dominant in fixed income portfolios (along with municipals for taxable investors). There were high yield bonds, but those were typically “fallen angels” rather than newly issued bonds. Mortgage-backed bonds didn’t exist because securitization of mortgages was just beginning. Today, Treasuries represent less than 16 percent of the U.S. bond market and corporate bonds another 20 percent. Chapter 7 examines this modern fixed income market in detail. In Chapter 8, all of these traditional assets are combined in what we call a strategic asset allocation, a long-run portfolio allocation based on long-run returns.

The returns on bonds have varied widely over the last few decades, so the chapter will investigate the main determinants of bond returns. Bonds are often favored by investors because they provide fixed income in contrast to the variable returns offered by equities and by most other assets. A stream of fixed income payments is often viewed as essential to retirees as well as many institutional investors because of their need for continual income. Investors focusing only on yields, however, are too often disappointed by the overall performance of their investments. Bond yields represent part of the total return to fixed income assets, but the variation in yields over time leads to capital gains and losses that sometimes dominate the total return from holding bonds. That’s especially true if the total return takes into account changes in the cost of living.

But the dispersion in performance across managers is much too large to be explained by whether one strategy, such as market-neutral equity, is chosen rather than another, like fixed-income arbitrage. Generating alpha is not easy, especially not the large alphas that are found for some hedge funds. To investigate the dispersion in manager performance, it’s helpful to compare hedge funds with other types of investments. That’s exactly what Malkiel and Saha (2004) did in the working paper version of the study cited earlier. Using TASS data for hedge fund managers and Lipper data for mutual fund managers, they calculated the returns of the top quartile and third quartile managers for each of five asset classes. These were hedge funds and four types of mutual funds for real estate, international equity, U.S. equity, and U.S. fixed income. Figure 9.5 reports the excess returns of the first quartile and third quartile managers over the median manager for that asset class.


pages: 353 words: 88,376

The Investopedia Guide to Wall Speak: The Terms You Need to Know to Talk Like Cramer, Think Like Soros, and Buy Like Buffett by Jack (edited By) Guinan

Albert Einstein, asset allocation, asset-backed security, Brownian motion, business cycle, business process, buy and hold, capital asset pricing model, clean water, collateralized debt obligation, computerized markets, correlation coefficient, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, discounted cash flows, diversification, diversified portfolio, dividend-yielding stocks, dogs of the Dow, equity premium, fixed income, implied volatility, index fund, intangible asset, interest rate swap, inventory management, London Interbank Offered Rate, margin call, money market fund, mortgage debt, Myron Scholes, passive investing, performance metric, risk tolerance, risk-adjusted returns, risk/return, shareholder value, Sharpe ratio, short selling, statistical model, time value of money, transaction costs, yield curve, zero-coupon bond

Investopedia explains Fixed Annuity A fairly good financial instrument for those seeking fixed investment income; this is particularly attractive to retirees. Related Terms: • Annuity • Defined-Benefit Plan • Income Statement • Individual Retirement Account—IRA • Mutual Fund Fixed-Income Security What Does Fixed-Income Security Mean? An investment that provides income in the form of fixed periodic payments and the eventual return of principal at maturity. Unlike a variable-income security, in which payments change on the basis of an underlying measure such as short-term interest rates, the payments of a fixed-income security are known in advance and do not change. Investopedia explains Fixed-Income Security An example of a fixed-income security would be a 5% fixed-rate government bond in which a $1,000 investment would result in an annual $50 payment until maturity, at which time the investor would receive the $1,000 back.

Related Terms: • Bankruptcy • Debt • Subprime Meltdown • Bear Market • Recession Credit Default Swap (CDS) What Does Credit Default Swap (CDS) Mean? A swap designed to transfer the credit exposure of fixed-income products between parties. Investopedia explains Credit Default Swap (CDS) The buyer of a credit swap receives credit protection, whereas the seller of the swap guarantees the creditworthiness of the product. When this is done, the risk of default is transferred from the holder of the fixed-income security to the seller of the swap. For example, the buyer of a credit swap still is entitled to the par value of the bond from the seller of the swap if the bond defaults in its coupon payments. 58 The Investopedia Guide to Wall Speak Related Terms: • Bond • Fixed Income Security • Swap • Credit Derivative • Interest Rate Swap Credit Derivative What Does Credit Derivative Mean?

Bankruptcy filings vary widely from country to country, leading to higher or lower filing rates, depending on how easily a person or company can complete the process. Related Terms: • Bear Market • Credit Crunch • Subprime Loan • Chapter 11 • Debt Basis Point (BPS) What Does Basis Point (BPS) Mean? A unit equal to 1/100 of 1%; it is used to denote a change in a financial instrument (usually a fixed-income security). The basis point is used commonly for calculating changes in interest rates, equity indexes, and the yield of a fixed-income security. 20 The Investopedia Guide to Wall Speak Investopedia explains Basis Point (BPS) Converting percentage changes in basis points is done as follows: 1% change = 100 basis points, and 0.01% = 1 basis point. Thus, a bond whose yield increases from 5% to 5.5% is said to increase by 50 basis points; when interest rates rise 1%, they have increased by 100 basis points.


pages: 243 words: 77,516

Straight to Hell: True Tales of Deviance, Debauchery, and Billion-Dollar Deals by John Lefevre

airport security, blood diamonds, buy and hold, colonial rule, credit crunch, fixed income, Goldman Sachs: Vampire Squid, high net worth, income inequality, jitney, lateral thinking, market clearing, Occupy movement, Sloane Ranger, the market place

I had no idea where the Twitter account would take me, but I did know that I had been collecting stories (the inane and insane) over the course of my career in banking. I joined the fixed-income desk of Salomon Brothers immediately out of college. *Starting in the wake of the dot-com bubble bursting and working through the financial crisis, across three continents, I enjoyed a colorful career during a turbulent and defining period in the history of financial markets and our society in general. * I joined the fixed-income desk of Salomon Brothers immediately out of college. I say Salomon as opposed to Citigroup or Salomon Smith Barney because the legal entity that employed me was technically Salomon Brothers International, and also to reflect the fact that the culture within fixed income was still very different than the rest of the bank. As “one of the most prolific syndicate managers in Asia,” I saw it all.

Then, after a final-round interview superday with Bear Stearns, I inadvertently sent a thank-you email to the head of emerging markets, telling him how much I wanted to work for JPMorgan. During a Goldman Sachs interview, some asshole asked me who, living or dead, I would most like to have dinner with. I guess he wasn’t particularly impressed that I named Tupac Shakur ahead of Marcus Aurelius or Alexander Hamilton. Still, despite these hiccups, in the end, I wanted to do fixed income, and for that, there was arguably no better place to be than Salomon Brothers, with the recently added platform and balance sheet of Citigroup behind it. There’s only one slight problem: my analyst class is the largest in the history of investment banking. We were hired based on quotas set in mid-2000, before it was evident that the dot-com party was over. Nowhere is this more painfully clear than in the European TMT team (telecom, media, and technology), which hired forty first-year analysts.

I’m not one for name tags and meet and greets, but there is certainly a business case to be made for getting to know all the kids in my class. For the final day of training, the firm puts on a celebratory pep rally in the auditorium of 388 Greenwich Street. Bigwigs like Mark Simonian (global head of TMT), Sir Deryck Maughan (chairman and former CEO of Salomon Brothers), Michael Klein (head of investment banking), and Tom Maheras (head of fixed income) each deliver rousing speeches about how there’s no firm in the world they’d rather work for and no better place for us to start our careers. Now we feel like we’ve made it—all 272 of us who remain. Having arrived late, I’m stuck in the back with a middle seat that will make it impossible to slip out unnoticed. Shortly after we begin, a kid I sort of know a few rows in front of me gets up and tries to make an exit.


pages: 430 words: 140,405

A Colossal Failure of Common Sense: The Inside Story of the Collapse of Lehman Brothers by Lawrence G. Mcdonald, Patrick Robinson

asset-backed security, bank run, business cycle, collateralized debt obligation, corporate raider, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, cuban missile crisis, diversification, fixed income, high net worth, hiring and firing, if you build it, they will come, London Interbank Offered Rate, Long Term Capital Management, margin call, money market fund, moral hazard, mortgage debt, naked short selling, negative equity, new economy, Ronald Reagan, short selling, sovereign wealth fund, value at risk

.: chairman of the board and chief executive officer Joseph Gregory: president and chief operating officer David Goldfarb: former chief financial officer; former global head of principal investing; chief strategy officer Christopher O’Meara: chief financial officer, 2005–07; chief risk officer Erin Callan: managing director and head of hedge fund investment banking; chief financial officer, 2007–08 George Walker IV: managing director and global head of investment management Ian Lowitt: chief administrative officer; chief financial officer, 2008 Lehman Brothers (Traders, Investment Bankers, Risktakers, Salespeople) Michael Gelband: managing director and global head of fixed income; head of capital markets; member of the executive committee Alex Kirk: managing director and global head of high-yield and leveraged-loan businesses; chief operating officer of fixed income; global head of principal investing Herbert “Bart” McDade: managing director and global head of fixed income; global head of equities; president, 2008; member of the executive committee Eric Felder: managing director and head of global credit products group; global head of fixed income Dr. Madelyn Antoncic: managing director and chief risk officer; government liaison Thomas Humphrey: managing director and global head of fixed-income sales Hugh “Skip” McGee: managing director and global head of investment banking Richard Gatward: managing director and global head of convertible trading and sales Lawrence E.

Except when I stand right here and look up at the great glass fortress which once housed Lehman, and focus on that thirty-first floor. Then it’s clear. Boy is it ever clear. And the phrase if only slams into my brain. If only they had listened—Dick Fuld and his president, Joe Gregory. Three times they were hit with the irredeemable logic of three of the cleverest financial brains on Wall Street—those of Mike Gelband, our global head of fixed income, Alex Kirk, global head of distressed trading research and sales, and Larry McCarthy, head of distressed-bond trading. Each and every one of them laid it out, from way back in 2005, that the real estate market was living on borrowed time and that Lehman Brothers was headed directly for the biggest subprime iceberg ever seen, and with the wrong men on the bridge. Dick and Joe turned their backs all three times.

Everyone I met was a class act. And then on the morning of July 14, 2004, a letter dropped into the mailbox at my apartment on Forest Street in Stamford. It came from the office of a Lehman vice president I had met, Deborah Millstein. Its words swam before my eyes: Dear Lawrence: We are pleased to extend to you our offer of employment to join Lehman Brothers Inc as a trader in the High Yield Department in the Fixed Income Division, reporting initially to Larry McCarthy and Richard Gatward. Your title of vice president will be submitted for official approval by the Executive Committee of our Board of Directors … How about that? Into the hierarchy, alongside some of Wall Street’s smartest guys. Sixteen years had passed since I’d been rejected by more brokerage houses than any other applicant in history. And now one of the biggest had finally seen the light.


pages: 354 words: 26,550

High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems by Irene Aldridge

algorithmic trading, asset allocation, asset-backed security, automated trading system, backtesting, Black Swan, Brownian motion, business cycle, business process, buy and hold, capital asset pricing model, centralized clearinghouse, collapse of Lehman Brothers, collateralized debt obligation, collective bargaining, computerized trading, diversification, equity premium, fault tolerance, financial intermediation, fixed income, high net worth, implied volatility, index arbitrage, information asymmetry, interest rate swap, inventory management, law of one price, Long Term Capital Management, Louis Bachelier, margin call, market friction, market microstructure, martingale, Myron Scholes, New Journalism, p-value, paper trading, performance metric, profit motive, purchasing power parity, quantitative trading / quantitative finance, random walk, Renaissance Technologies, risk tolerance, risk-adjusted returns, risk/return, Sharpe ratio, short selling, Small Order Execution System, statistical arbitrage, statistical model, stochastic process, stochastic volatility, systematic trading, trade route, transaction costs, value at risk, yield curve, zero-sum game

Optimal Trading Frequency 1 Year 1 Month 1 Day Private Equity Small-Cap Equities Commodities 1 Hour Options 1 Minute 1 Second Futures Large-Cap Equities ExchangeTraded Options Fixed-Income ETFs Foreign Exchange Instrument liquidity (daily trading volume) FIGURE 4.1 Optimal trading frequency for various trading instruments, depending on the instrument’s liquidity. 40 HIGH-FREQUENCY TRADING Fixed-Income Markets The fixed-income markets include the interest rate market and the bond market. The interest rate market trades short- and long-term deposits, and the bond market trades publicly issued debt obligations. Interest rate products and bonds are similar in that they both pay fixed or prespecified income to their holders. Aside from their fixed-income quality, bonds and interest rate products exhibit little similarity. Both interest rate and bond markets use spot, futures, and swap contracts.

According to research conducted by Aite Group, equities are the most algorithmically 19 Evolution of High-Frequency Trading 60% 50% Equities Futures Options FX Fixed Income 40% 30% 20% 10% 0% 2004 2005 2006 2007 2008 2009 2010 Year FIGURE 2.7 Adoption of algorithmic execution by asset class. Source: Aite Group. executed asset class, with over 50 percent of the total volume of equities expected to be handled by algorithms by 2010. As Figure 2.7 shows, equities are closely followed by futures. Advances in algorithmic execution of foreign exchange, options, and fixed income, however, have been less visible. As illustrated in Figure 2.7, the lag of fixed income instruments can be explained by the relative tardiness of electronic trading development for them, given that many of them are traded OTC and are difficult to synchronize as a result.

Macroeconomic news arrives from every corner of the world. The impact on currencies, commodities, equities, and fixed-income and derivative instruments is usually estimated using event studies, a technique that measures the persistent impact of news on the prices of securities of interest. APPLICATION OF EVENT ARBITRAGE Foreign Exchange Markets Market responses to macroeconomic announcements in foreign exchange were studied by Almeida, Goodhart, and Payne (1998); Edison (1996); Andersen, Bollerslev, Diebold, and Vega (2003); and Love and Payne (2008), among many others. Edison (1996) studied macroeconomic news impact on daily changes in the USD-based foreign exchange rates and selected fixed-income securities, and finds that foreign exchange reacts most significantly to news about real economic activity, such as non-farm payroll employment figures. 176 HIGH-FREQUENCY TRADING TABLE 12.2 Ex-Ante Schedule of Macroeconomic Announcements for March 3, 2009 Consensus Forecast Time (ET) Event Prior Value Country 1:00 A.M.


pages: 543 words: 157,991

All the Devils Are Here by Bethany McLean

Asian financial crisis, asset-backed security, bank run, Black-Scholes formula, Blythe Masters, break the buck, buy and hold, call centre, collateralized debt obligation, corporate governance, corporate raider, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, Exxon Valdez, fear of failure, financial innovation, fixed income, high net worth, Home mortgage interest deduction, interest rate swap, laissez-faire capitalism, Long Term Capital Management, margin call, market bubble, market fundamentalism, Maui Hawaii, money market fund, moral hazard, mortgage debt, Northern Rock, Own Your Own Home, Ponzi scheme, quantitative trading / quantitative finance, race to the bottom, risk/return, Ronald Reagan, Rosa Parks, shareholder value, short selling, South Sea Bubble, statistical model, telemarketer, too big to fail, value at risk, zero-sum game

He pushed Goldman to begin trading options, which it had long shied away from, even hiring Fischer Black, the MIT professor and coinventor of the famous Black-Scholes options pricing model. Goldman’s options trading desk soon became immensely profitable as well. As co-head of the fixed-income research department in the mid-1980s, Rubin helped transform the fixed-income division from a second-tier player into a worthy competitor to such bond strongholds as Salomon Brothers and First Boston. By 1990, he was the co-head of the entire firm. (He shared the title with Steve Friedman, who had also run the fixed-income department with him.) By the time Rubin left for the Clinton administration in 1993—where he spent two years as the head of the National Economic Council before becoming Treasury secretary—Goldman had become the envy of Wall Street.

Kim quickly assured the rest of the CDO staff that the firm would do “whatever it takes” to stay number one. He said the same to Stan O’Neal. A few months later, in April, Merrill’s directors and top executives went to Pebble Beach for an off-site. During one of the working sessions, the discussion centered on Merrill’s fixed-income department. “The world has changed,” O’Neal told the assembled executives, according to several people who were there. Fixed income and credit, he added, were no longer cyclical in nature. There was going to be an ongoing demand for fixed-income products. “We need to continue our ability to take risk and manufacture products,” he said. By then, Kronthal was beginning to fear the mortgage market was becoming overheated. His bosses, starting with O’Neal, felt otherwise. They wanted more people like Ricciardi, not fewer.

He hated—hated—losing, whether he was on the ski slopes or trying to land a deal. Unlike his predecessor, Corzine, or his eventual successor, Lloyd Blankfein, Paulson was an investment banker, not a fixed-income trader; he had spent the early part of his career doing banking deals out of Goldman’s Chicago office. (Prior to joining Goldman, Paulson had served as an assistant to John Ehrlichman in the Nixon administration.) He became a partner in 1982, eight years after joining the firm, rising to be co-head of the firm’s investment banking department and then its chief operating officer before taking over as CEO in 1999. Investment banker though he was, Paulson did not try to turn back the clock. He saw clearly that trading and fixed income weren’t just the future of the firm—they were the present. The last hurrah for the investment bankers at Goldman had been the Internet bubble, which burst in early 2000, not long after Paulson took control of the firm.


pages: 290 words: 83,248

The Greed Merchants: How the Investment Banks Exploited the System by Philip Augar

Andy Kessler, barriers to entry, Berlin Wall, Big bang: deregulation of the City of London, Bonfire of the Vanities, business cycle, buttonwood tree, buy and hold, capital asset pricing model, commoditize, corporate governance, corporate raider, crony capitalism, cross-subsidies, financial deregulation, financial innovation, fixed income, Gordon Gekko, high net worth, information retrieval, interest rate derivative, invisible hand, John Meriwether, Long Term Capital Management, Martin Wolf, new economy, Nick Leeson, offshore financial centre, pensions crisis, regulatory arbitrage, Sand Hill Road, shareholder value, short selling, Silicon Valley, South Sea Bubble, statistical model, Telecommunications Act of 1996, The Chicago School, The Predators' Ball, The Wealth of Nations by Adam Smith, transaction costs, tulip mania, value at risk, yield curve

In the early 1980s Lehman came close to falling apart in a divisive power struggle between investment banking and securities. In 1984 American Express bought Lehman, then principally an investment banking and institutional fixed income firm, and merged it with Shearson, principally a retail firm. The cultures never mixed and in 1993, when American Express decided to get out of the investment business, the retail part was sold to Smith Barney, which was then absorbed by Citigroup. Lehman re-emerged as an independent listed company in 1994. But that year, a bear market in fixed income bond trading hit Lehman’s main business. At this time I was in charge of NatWest’s debt and equity broking business and Lehman’s treasurer came to see me on a mission to keep the firm’s credit lines open; we supported them but it was a close call.

It was all about getting volume; now it’s all about margin, making sure there is one.’17 When equity revenues dried up the investment banks quickly switched to fixed income, which grew from being a third of profits in 2000 to two-thirds in 2002. They were helped by favourable market conditions. As interest rates fell to their lowest levels since the 1960s, corporate treasurers rushed to borrow money and to refinance debt at low interest rates. The investment banks were there in a flash, pitching new bond and bond derivatives issues and selling them to fund managers. The yield curve was steep and the proprietary trading departments were able to borrow short, invest long and pick up a huge interest carry. Fixed income people, out of the limelight during the equities bull market, suddenly found themselves the flavour of the month and gained in power, influence and compensation: ‘Bond traders who not long ago were considered second class citizens by their colleagues in investment banking and equities were now back on top of the social pile.’18 The growth of the hedge fund industry also illustrates the investment banks’ ability to latch on to new trends and work up a business around them.

In 2004 I asked a former Morgan Stanley managing director, a person who had headed up one of its big divisions, to look back on the firm’s history: ‘Morgan Stanley has been on a run of uninterrupted success since the early seventies. The key decision at that time was to retain capital in the firm to build securities rather than distribute it to partners. Then in 1986 the firm went public and was in effect recapitalized. During the eighties we made fewer mistakes than our competitors. We expanded overseas more intelligently, exporting our fixed income skills to Europe and Japan. The loss of Gleacher and Greenhill was an issue but never caused an implosion of the kind that hit First Boston when Wasserstein and Perella left there.* Morgan Stanley has longevity of management and consistency of strategy. Parker Gilbert hands over to Dick Fisher, Dick Fisher hands over to John Mack and so on. There is more continuity than disruption. We husbanded our reputation very carefully.


pages: 297 words: 91,141

Market Sense and Nonsense by Jack D. Schwager

3Com Palm IPO, asset allocation, Bernie Madoff, Brownian motion, buy and hold, collateralized debt obligation, commodity trading advisor, computerized trading, conceptual framework, correlation coefficient, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, diversified portfolio, fixed income, high net worth, implied volatility, index arbitrage, index fund, London Interbank Offered Rate, Long Term Capital Management, margin call, market bubble, market fundamentalism, merger arbitrage, negative equity, pattern recognition, performance metric, pets.com, Ponzi scheme, quantitative trading / quantitative finance, random walk, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, selection bias, Sharpe ratio, short selling, statistical arbitrage, statistical model, survivorship bias, transaction costs, two-sided market, value at risk, yield curve

Table 3.2 HFRI Hedge Fund Strategy Indexes* Index 1 HFRI Equity Hedge (Total) Index 2 HFRI Equity Hedge: Equity Market Neutral Index 3 HFRI Equity Hedge: Quantitative Directional 4 HFRI Equity Hedge: Sector—Energy/Basic Materials Index 5 HFRI Equity Hedge: Sector—Technology/Health Care Index 6 HFRI Equity Hedge: Short Bias Index 7 HFRI Event-Driven (Total) Index 8 HFRI Event-Driven: Distressed/Restructuring Index 9 HFRI Event-Driven: Merger Arbitrage Index 10 HFRI Event-Driven: Private Issue/Regulation D Index 11 HFRI Macro (Total) Index 12 HFRI Macro: Systematic Diversified Index 13 HFRI Relative Value (Total) Index 14 HFRI Relative Value: Fixed Income—Asset Backed 15 HFRI Relative Value: Fixed Income—Convertible Arbitrage 16 HFRI Relative Value: Fixed Income—Corporate Index 17 HFRI Relative Value: Multi-Strategy Index 18 HFRI Relative Value: Yield Alternatives Index 19 HFRI Emerging Markets (Total) Index 20 HFRI Emerging Markets: Asia ex-Japan Index 21 HFRI Emerging Markets: Global Index 22 HFRI Emerging Markets: Latin America Index 23 HFRI Emerging Markets: Russia/Eastern Europe Index *Excludes fund of fund indexes, which combine multiple strategies.

Statistical arbitrage involves highly frequent trading activity, with trades lasting between seconds and days. Fixed income arbitrage. This strategy seeks to profit from perceived mispricings between different interest rate instruments. Positions are balanced to maintain neutrality to changes in the broad interest rate level, but may express directional biases in terms of the yield curve—anticipated changes in the yield relationship between short-term, medium-term, and long-term interest rates. As an example of a fixed income arbitrage trade, if five-year rates were viewed as being relatively low versus both shorter- and longer-term rates, the portfolio manager might initiate a three-legged trade of long two-year Treasury notes, short five-year T-notes, and long 10-year T-notes, with the position balanced so that it was neutral to parallel shifts in the yield curve. Fixed income arbitrage normally requires the use of substantial leverage because the relative price aberrations it seeks to exploit tend to be small.

During these events, steeply declining values in high-yielding debt securities (e.g., junk bonds, emerging market bonds) can lead to capital losses far greater than the yield differential earned. Note, for example, in Figure 4.4 the sustained negative returns in the HFR Fixed Income Corporate Index (an index of credit hedge funds) from mid-2007 through early 2009, coincident with the sharp widening of credit spreads. In these instances, credit risk and leverage risk will exhibit a negative synergistic effect, as the larger the leverage, the greater the credit investment losses. Figure 4.4 HFR Fixed Income Corporate Index Monthly Returns (Six-Month Average) versus Credit Spread (Moody’s Baa Yield Minus 10-Year Treasury Note Yield) In all these instances (except perhaps for market risk, where adverse periods may be more frequent), strategies prone to the foregoing event risks will exhibit relatively smooth performance and limited equity drawdowns during most periods, interspersed with occasional episodes of large drawdowns.


pages: 362 words: 108,359

The Accidental Investment Banker: Inside the Decade That Transformed Wall Street by Jonathan A. Knee

barriers to entry, Boycotts of Israel, call centre, cognitive dissonance, commoditize, corporate governance, Corrections Corporation of America, discounted cash flows, fear of failure, fixed income, greed is good, if you build it, they will come, iterative process, market bubble, market clearing, Menlo Park, new economy, Ponzi scheme, pre–internet, risk/return, Ronald Reagan, shareholder value, Silicon Valley, technology bubble, young professional, éminence grise

The next morning I stopped in to Mitch’s office on my way out to get the official approval. “I’m waiting to hear back from George,” Mitch said. “Who the hell is George?” I asked. George James, I learned, was Mitch’s immediate supervisor in the new fixed income hierarchy. “Just call me from the car,” he said, “don’t worry about it.” So I called from the car. “George wants to talk to Zoe,” Mitch informed me, referring to Zoe Cruz, who was in charge of all of Fixed Income. “It should just be a few minutes.” Just before entering the board meeting I ducked into a private phone booth across the hall. “Zoe needs to speak with Vikram.” Vikram was co-head of the Institutional Securities Division into which Fixed Income reported. “You have got to be kidding me!” I cried. “None of these fucking people are even on the Commitments Committee! Why did we even bother?” Luckily, the board meeting would run several hours, with the financing issues not covered until well into the agenda.

But, despite the intrinsic profitability of junk, the investment banking leaders liked to be associated with names like Ford and AT&T rather than the cash-strapped Chrysler or the start-up McCaw Cellular. This conflicted attitude created an opening for a niche player to take the leading position in this attractive business. What sends an investment banking firm into decline is typically a major scandal, a capital crisis, a mass exodus of productive partners or, usually, some combination of the three. Salomon Brothers, using street smarts and creative structuring particularly in the fixed income markets, had clawed its way to the top of the overall financing league tables in the 1980s. The downside of its out-of-control trading culture would be well documented in Michael Lewis’ Liar’s Poker, in which the author wrote about his experience as a young bond salesman in the years leading up to the crash of 1987. But by the late 1980s cracks in Salomon’s armor began to show. Lew Ranieri, the brilliant architect of Salomon’s once highly profitable mortgage-backed trading operations, left in 1987.

Still, 25 years later in 1994, Goldman had managed to avoid most of the major pitfalls that by then had forced other private investment banking partnerships to sell out, shut down, or go public. Discord between the banking and trading sides of the house had torn a number of the old partnerships asunder. But Goldman had grown up as a commercial paper operation. Marcus Goldman started by literally walking the streets stuffing IOUs from merchants into his hat and trading them to a bank at day’s end. So the tensions between banking and fixed income trading never reached the fever pitch it had elsewhere. Leadership also moved from banker (Sidney Weinberg) to trader (Gus Levy) to partnerships that typically included one of each (Robert Rubin/Steve Friedman) demonstrating an institutional respect for both. Furthermore, at least since the departure of Catchings in the 30s, the strength of Goldman’s leadership and thoughtfulness of the succession planning had kept the culture strong and smoothed any divisions.


Commodity Trading Advisors: Risk, Performance Analysis, and Selection by Greg N. Gregoriou, Vassilios Karavas, François-Serge Lhabitant, Fabrice Douglas Rouah

Asian financial crisis, asset allocation, backtesting, buy and hold, capital asset pricing model, collateralized debt obligation, commodity trading advisor, compound rate of return, constrained optimization, corporate governance, correlation coefficient, Credit Default Swap, credit default swaps / collateralized debt obligations, discrete time, distributed generation, diversification, diversified portfolio, dividend-yielding stocks, fixed income, high net worth, implied volatility, index arbitrage, index fund, interest rate swap, iterative process, linear programming, London Interbank Offered Rate, Long Term Capital Management, market fundamentalism, merger arbitrage, Mexican peso crisis / tequila crisis, p-value, Pareto efficiency, Ponzi scheme, quantitative trading / quantitative finance, random walk, risk-adjusted returns, risk/return, selection bias, Sharpe ratio, short selling, stochastic process, survivorship bias, systematic trading, technology bubble, transaction costs, value at risk, zero-sum game

Her principal research interest is in production analysis and issues relating to mergers, productivity, efficiency, as well as regional differences in competitiveness and productivity growth. Her published work has appeared in several peer-reviewed journals. Nicolas Papageorgiou is an Assistant Professor in the Department of Finance at the Hautes études commerciales (HEC), University of Montreal, Canada. His main research interests and publications deal with fixed income securities, specifically the pricing of structured products and the analysis of fixed income arbitrage strategies used by hedge fund managers. About the Authors xxi Dr. Papageorgiou has taught graduate-level courses in Canada and the U.K. and has presented at numerous academic and practitioner conferences in North America, Europe, and North Africa. Kok Fai Phoon is Executive Director Designate, Ferrell Asset Management. He holds a Ph.D. in Finance from Northwestern University.

Hilary Till is cofounder and Portfolio Manager at Premia Capital Management, LLC, in Chicago, which specializes in detecting pockets of predictability in derivatives markets by using statistical techniques. Ms. Till is also a Principal of Premia Risk Consultancy, Inc., which advises investment firms on derivatives strategies and risk management policy. Prior to Premia, Ms. Till was Chief of Derivatives Strategies at Boston-based Putnam Investments, where she was responsible for the management of all derivatives investments in domestic and international fixed income, tax-exempt fixed income, foreign exchange, and global asset allocation. Prior to Putnam Investments, Ms. Till was a Quantitative Equity Analyst at Harvard Management Company (HMC) in Boston, the investment management company for Harvard University’s endowment. She holds a B.A. in Statistics from the University of Chicago and a M.Sc. in Statistics from the London School of Economics. Her articles on derivatives, risk management, and alternative investments have been published in several peer-reviewed academic journals.

They concluded that managed futures may offer some of the hedging properties of a put option at a lower cost.1 1Schneeweis and Spurgin (1998b) used a dollar-weighted index of CTAs published by Managed Account Reports (MAR). 338 PROGRAM EVALUATION, SELECTION, AND RETURNS Schneeweis and Spurgin (1998b) further presented evidence that hedge funds and managed futures may improve the risk-return profiles of equity, fixed income, as well as traditional alternative investments such as risky debt. Their findings were based on correlation analysis between the underlying factors of: ■ ■ ■ ■ Hedge fund indices from Hedge Fund Research and Evaluation Associates Capital Management (EACM) CTA indices (from MarHedge, Barclay Trading, and EACM) S&P 500 and MSCI World indices for equities Salomon Brothers Government Bond and World Government Bond indices for fixed income securities Kat (2002) studied the possible role of managed futures in portfolios of stocks, bonds, and hedge funds. He found that managed futures appear to be more effective diversifiers than hedge funds.


How I Became a Quant: Insights From 25 of Wall Street's Elite by Richard R. Lindsey, Barry Schachter

Albert Einstein, algorithmic trading, Andrew Wiles, Antoine Gombaud: Chevalier de Méré, asset allocation, asset-backed security, backtesting, bank run, banking crisis, Black-Scholes formula, Bonfire of the Vanities, Bretton Woods, Brownian motion, business cycle, business process, butter production in bangladesh, buy and hold, buy low sell high, capital asset pricing model, centre right, collateralized debt obligation, commoditize, computerized markets, corporate governance, correlation coefficient, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, discounted cash flows, disintermediation, diversification, Donald Knuth, Edward Thorp, Emanuel Derman, en.wikipedia.org, Eugene Fama: efficient market hypothesis, financial innovation, fixed income, full employment, George Akerlof, Gordon Gekko, hiring and firing, implied volatility, index fund, interest rate derivative, interest rate swap, John von Neumann, linear programming, Loma Prieta earthquake, Long Term Capital Management, margin call, market friction, market microstructure, martingale, merger arbitrage, Myron Scholes, Nick Leeson, P = NP, pattern recognition, Paul Samuelson, pensions crisis, performance metric, prediction markets, profit maximization, purchasing power parity, quantitative trading / quantitative finance, QWERTY keyboard, RAND corporation, random walk, Ray Kurzweil, Richard Feynman, Richard Stallman, risk-adjusted returns, risk/return, shareholder value, Sharpe ratio, short selling, Silicon Valley, six sigma, sorting algorithm, statistical arbitrage, statistical model, stem cell, Steven Levy, stochastic process, systematic trading, technology bubble, The Great Moderation, the scientific method, too big to fail, trade route, transaction costs, transfer pricing, value at risk, volatility smile, Wiener process, yield curve, young professional

My work on that first project provided me with considerable insight into how interest rates moved, and how no-arbitrage arguments led to option pricing models. It also helped me begin to understand how interest rate option models fit into the larger-risk model, and how investors used that model. But my knowledge of finance at that time was an inch wide and a mile deep. I knew the Cox, Ingersoll, Ross model in considerable detail. And that was almost all I knew in finance. In October 1987, after eight months at BARRA, I attended my first Fixed Income Research Seminar at Pebble Beach. I presented an optional session on my work. Richard instructed everyone to only let me talk to the most technically sophisticated clients. Although I could discuss technical details about option models, I would have struggled with more general questions. JWPR007-Lindsey May 7, 2007 16:30 38 h ow i b e cam e a quant Success in finance would require me to acquire much more intuition and insight into the basic problems faced by investors and to build up a toolkit for analyzing those problems.

When he became executive vice president, I became director of research, a role I held for over seven years. Richard left BARRA at the end of 1992 to join Wells Fargo Nikko Investment Advisors, which later became Barclays Global Investors (BGI). My years as director of research at BARRA were fantastic in terms of my intellectual development. I worked on many interesting projects, including supervising the development of new equity, fixed income, and trading models. Beyond researching new BARRA products, I participated in numerous research studies that appeared as seminar presentations and subsequent articles. Andrew Rudd and I analyzed that ultimate question for investors: Does historical performance predict future performance?12 Our contributions included better quantitative applesto-apples comparisons of managers, and an analysis of whether any perceived persistence of performance could lead to an outperforming investment strategy.

I had grown up eating New-York style pizza my whole life and never saw anyone “blot” a slice. So, I grabbed my own handful of napkins and proceeded to do the same, at which point he exclaimed, “Wow, I never saw anyone else do that before – I thought I was the only one!” I got the job. My work during that next year was incredibly rewarding. The focus of the fund was to create automated trading strategies and apply them to global futures markets, including commodities, equities, and fixed income. As long as it was a valid futures market, we traded it, regardless if the prices represented Eurodollar contracts or Red Azuki Beans. I spent a lot of time writing very complex code to create and backtest different types of trading strategies using daily futures data back to the 1940s. Oodles of data, challenging analyses, and lots of programming— this is exactly what I had been doing in physics for a dozen years, and I was groovin’.


Trading Risk: Enhanced Profitability Through Risk Control by Kenneth L. Grant

backtesting, business cycle, buy and hold, commodity trading advisor, correlation coefficient, correlation does not imply causation, delta neutral, diversification, diversified portfolio, fixed income, frictionless, frictionless market, George Santayana, implied volatility, interest rate swap, invisible hand, Isaac Newton, John Meriwether, Long Term Capital Management, market design, Myron Scholes, performance metric, price mechanism, price stability, risk tolerance, risk-adjusted returns, Sharpe ratio, short selling, South Sea Bubble, Stephen Hawking, the scientific method, The Wealth of Nations by Adam Smith, transaction costs, two-sided market, value at risk, volatility arbitrage, yield curve, zero-coupon bond

See also Stop-out level Exposure adjustment strategies: directional bias, 135–141 diversification, 144–146 leverage, 146–148 optionality, 148–153 position level volatility, 141–142 position size, 134–135 time horizon, 142–144 Exposure range determination: components of, 110–111 inverted Sharpe Ratio, 111–114, 248–250 volatility management, as trading capital percentage, 114–126 Fat tails, 116, 118 Federal Reserve Regulation T, 148 Financial statements, 185, 225 Fixed-income market, 145 Fixed-income portfolio, 147 INDEX Fixed-income trading, 56, 74, 105 Front-running, 196–197 Fully invested risk position, 227 Futures/futures market, 56, 185, 239–240 Games of chance, 247–248 “Going to the beach,” 32–36 Gross market value, 161 Harvard Matrix, 226 Hedge funds, 41, 119–120, 166, 194–195 Hedge-oriented trades, 139–140 Hedging, 151–152, 202 High-risk profile, 59 High-velocity trading strategies, 193 High-water approach, 71, 121 Histograms, 51–53 Historical volatility, 84–88, 96–97 Holding period: correlation analysis, 175–177 individual trades, 162–165 time horizon and, 142–144 trading with an edge, 222 “House,” being the, 223 Humor, importance of, 243–244 Impact ratio, 186–188 Implied volatility, 86–87, 89 Incremental risk, 126, 141–142 Individual portfolio, risk components: correlation, 90–91 historical volatility, 84–88, 96–97 options implied volatility, 86–89 scenario analysis, 104–106 technical analysis, 106–108 value at risk (VaR), 91–104 Individual trades, risk components of: core transactions-level statistics, 161–168, 209, 211 correlation analysis, 168–181 influential factors, generally, 208–211 performance ratio improvement methods, 189–208 performance success metrics, 184–189 transaction performance, 156–161 Index Ineffective risk management, 124–125 Information processing, 220–221 Institutional investments/traders, 29, 193 Instrument classes, 200 Interest rates, as influential factor, 87, 105 In-the-money option, 150 Intraday prices, 39 Intraday P/L, 42 Intraday trading, 162 Intrinsic value, 87, 150 Inverted Sharpe Ratio, 111–114, 248–250 Investment.

., without regard to market direction), a given market-neutral, long/short portfolio with very minimal risk has a higher degree of leverage than one that simply contained the long positions in the same portfolio––in spite of the fact that the latter is likely to be the more risky market profile. Beyond this, leverage statistics have vastly different implications across asset classes and across instrument classes within a given asset class. For example, the use of a specified amount of leverage in a fixed-income portfolio will generally have lessacute impacts than will the same profile in equities, due to the fact that equity markets routinely have higher levels of volatility. For identical reasons, within the fixed-income group, leverage will be more impactful at the long end of the yield curve than it will for short-term trading instruments. Beyond this, certain derivative instrument classes are designed to engineer precise leverage for investors because they offer trade-offs that involve both the cost of the investment and the probability of their bringing about a favorable outcome.

The recommended attributes that should be included in the data set are: • • • • • • • • • Instrument name. Date and time of transaction. Buy/sell indicator. Price. Quantity. Executing broker/counterparty. Commission. Order type (e.g., market, limit, stop, etc.). Native currency denomination. In addition, depending on the type of instrument traded, it may be necessary to record: • • • • Maturity (for fixed income) or expiration (for futures and options) date. Coupon rate and frequency (fixed income). Put/call indicator (for options). Strike price (for options). While these informational elements will more or less completely define a given transaction (at least for most types of trading), there are other indirect pieces of information that you need not record for each 158 TRADING RISK trade but that will be implicit in the information already gathered and that you should by all means include in your subsequent analysis.


The Handbook of Personal Wealth Management by Reuvid, Jonathan.

asset allocation, banking crisis, BRICs, business cycle, buy and hold, collapse of Lehman Brothers, correlation coefficient, credit crunch, cross-subsidies, diversification, diversified portfolio, estate planning, financial deregulation, fixed income, high net worth, income per capita, index fund, interest rate swap, laissez-faire capitalism, land tenure, market bubble, merger arbitrage, negative equity, new economy, Northern Rock, pattern recognition, Ponzi scheme, prediction markets, Right to Buy, risk tolerance, risk-adjusted returns, risk/return, short selling, side project, sovereign wealth fund, statistical arbitrage, systematic trading, transaction costs, yield curve

Advisory portfolio management, on the other hand, tends to be designed for clients wishing to retain more control over investment decisions – a more ‘hands-on’ approach. Figure 1.1.4, Investment involvement, shows a broad representation of the types of services differentials that exist between discretionary and advisory approaches. _________________________________________________ THE EYE OF THE NEEDLE 11 ឣ HFs: Macro/Managed Futures 6.0% HFs: Equity Long/short 2.4% Fixed Income – Inv. Grade (International) 18.2% HFs: Relative Value/Event Driven 8.4% Fixed Income – Inv. Grade (Local) 10.2% Fixed Income – High Yield 2.1% Equity 52.6% 11.0 0% Illiquidity 10% Illiquidity 20% Illiquidity 30% Illiquidity Expected Return (%) 10.0 9.0 Model V Model IV Model III 8.0 Model II 7.0 6.0 Model I 5.0 For Illustration Only 4.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 Expected Standard Deviation (%) Source: Citi Private Bank as at December 2008 Figure 1.1.3 Illustration line of optimal portfolio ‘fits’ This is provided as a generic illustration only and differences between service offerings will vary.

Table 1.3.1 Performance of hedge fund indices in 2008 Strategy Net of fees year to date returns to 31 Oct 08 (USD) HFRI Fund Weighted Composite Index HFRI Equity Hedge (Total) Index HFRI EH: Equity Market Neutral Index HFRI EH: Quantitative Directional HFRI EH: Short Bias Index HFRI Event-Driven (Total) Index HFRI ED: Merger Arbitrage Index HFRI Macro (Total) Index HFRI Relative Value (Total) Index HFRI RV: Fixed Income–Asset Backed HFRI RV: Fixed Income–Convertible Arbitrage Index HFRI RV: Fixed Income–Corporate Index HFRI RV: Multi–Strategy Index –15.48 –22.49 –3.78 –19.04 21.18 –16.66 –5.37 5.55 –17.11 0.07 –35.06 –18.32 –20.69 ________________________________________________ HEDGE FUND STRATEGIES 33 ឣ Discretionary macro Discretionary macro is one of the few strategies that has posted positive performance in the year to date (end October 2008).

Fundamental to the strategy is a stop-loss system that limits the downside should a trade go wrong. Keeping an eye on trading costs is also key as turnover is very high. Short-term CTAs must specialize in liquid markets, and often volatility and short-term trend reversals can aid performance; however rapid intrasession whipsawing may not be beneficial. Fixed income arbitrage This is an investment strategy that attempts to profit from mis-pricing in fixed income securities. Typically the arbitrageur will go long the under-priced security and short the over-priced security; a common trade is swap-spread arbitrage, which ឣ 28 PORTFOLIO INVESTMENT _________________________________________________ consists of taking opposing long and short positions in a swap and treasury bond. These strategies often produce very small returns and a large amount of leverage is required to produce meaningful results.


pages: 267 words: 71,941

How to Predict the Unpredictable by William Poundstone

accounting loophole / creative accounting, Albert Einstein, Bernie Madoff, Brownian motion, business cycle, butter production in bangladesh, buy and hold, buy low sell high, call centre, centre right, Claude Shannon: information theory, computer age, crowdsourcing, Daniel Kahneman / Amos Tversky, Edward Thorp, Firefox, fixed income, forensic accounting, high net worth, index card, index fund, John von Neumann, market bubble, money market fund, pattern recognition, Paul Samuelson, Ponzi scheme, prediction markets, random walk, Richard Thaler, risk-adjusted returns, Robert Shiller, Robert Shiller, Rubik’s Cube, statistical model, Steven Pinker, transaction costs

The first month that the PE moves above 24, make a note of the PE value. Don’t sell anything yet. Each month afterward, record the latest PE value. You sell only on a downturn. When the current month’s PE is at least 6 percent less than the highest monthly value since it rose above 24, sell your S&P 500 fund (or whatever fraction is being managed with this system) and put the money in safe fixed-income investments. Since you’ll probably have a permanent allocation to fixed income as well, you’ll need to keep a record of how much is the stock fund proceeds. Example. The Shiller PE is above 24 when you check in June. By November you’ve got this list: June, 24.03 July, 24.60 August, 24.41 September, 27.45 October, 27.32 November, 25.53 The highest value in the list is 27.45, for September. The current (November) value is 25.53, which is more than 6 percent short of the 27.45 maximum.

In August the highest value on the list was 24.60 for July (obviously you didn’t then have the values beyond August). The August pullback was only 1 percent from the July maximum and should not have triggered a sale. You remain parked in fixed-income investments until you get a buy signal. This will usually take several years. Keep checking the PE monthly. When it first dips below 15, note the month and PE. Each month thereafter, add the latest PE value to the list. Eventually there will be an upturn. When the current month’s PE is at least 6 percent above the recent low value, buy back into the stock index fund, using the proceeds of the fixed-income investments you bought at the previous sell signal (plus reinvested interest). With that the cycle renews. You go back to waiting for a sell signal. Meanwhile, reinvest dividends and capital gains distributions, and keep making contributions.

Even if it’s possible, they are more likely to lose than to profit from the attempt. As we’ve seen, there is ample evidence for that proposition. Lately the behavioral penalty has been co-opted by the mutual fund industry to promote buy-and-hold investing. They’re not entirely motivated by the public good. Fund managers collect fees only while investors own their funds. It’s easier to justify high fees for stock funds than fixed-income funds. Therefore, the fund industry is reluctant to admit that there might be times when it’s not worth owning stocks. They have concocted bogeyman stories to scare investors into buying-and-never-selling. One of the favorite pitches is that most of the stock market’s long-term return is due to a few halcyon days that post big gains. You don’t know when those days will be; ergo, you have to be fully invested all the time.


pages: 333 words: 76,990

The Long Good Buy: Analysing Cycles in Markets by Peter Oppenheimer

"Robert Solow", asset allocation, banking crisis, banks create money, barriers to entry, Berlin Wall, Big bang: deregulation of the City of London, Bretton Woods, business cycle, buy and hold, Cass Sunstein, central bank independence, collective bargaining, computer age, credit crunch, debt deflation, decarbonisation, diversification, dividend-yielding stocks, equity premium, Fall of the Berlin Wall, financial innovation, fixed income, Flash crash, forward guidance, Francis Fukuyama: the end of history, George Akerlof, housing crisis, index fund, invention of the printing press, Isaac Newton, James Watt: steam engine, joint-stock company, Joseph Schumpeter, Kickstarter, liberal capitalism, light touch regulation, liquidity trap, Live Aid, market bubble, Mikhail Gorbachev, mortgage debt, negative equity, Network effects, new economy, Nikolai Kondratiev, Nixon shock, oil shock, open economy, price stability, private sector deleveraging, Productivity paradox, quantitative easing, railway mania, random walk, Richard Thaler, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Shiller, Ronald Reagan, savings glut, secular stagnation, Simon Kuznets, South Sea Bubble, special economic zone, stocks for the long run, technology bubble, The Great Moderation, too big to fail, total factor productivity, trade route, tulip mania, yield curve

In the later phases of expansion, the best-performing assets remain equities, but these are dominated by equities with a higher beta, or those that tend to amplify movements in underlying fundamentals to a greater degree, such as EM equities. Commodities tend to be more neutral in this phase, and fixed income assets tend to underperform as a consequence of a higher investor tolerance for risk and, in most cases, higher inflation. In the early part of a recession, defensive assets start to outperform but oil tends to continue to do well as growth levels are still positive (albeit decelerating). In this phase, risky assets and most cyclical and high-beta equities tend to underperform most. Corporate debt has generally been a hybrid between a fixed income and equity asset, and generally does best in the latter part of the recessionary phase as bond yields fall and forward growth risks start to moderate. The response to inflation across assets is less straightforward than the relationship with growth, because asset performances vary materially depending on both levels of and changes in inflation.

The Reward for Risk and the Equity Risk Premium Comparing returns on bonds and equities enables us to look retrospectively at the reward for taking risk (investing in the unknown future return on equities compared with the fixed nominal return on bonds). Equities are on the riskier side of the investment range because equity investors have the last claim over a company's profits (after bond holders and other creditors). Equity therefore has an uncertain future return. It is possible for a company to lose money and the price of the stock can fall, or, worse still, the company can go bankrupt. For investors in fixed income assets (the income is known in nominal terms at the time of purchase), the risk is one of government or corporate default; lending to governments is generally much safer than lending to companies because it is more likely that a company will lose money or collapse entirely than a government default on its debt (although it is typically seen as riskier in emerging economies where there is often a history of default).

This relationship is encapsulated in the simple one-stage DDM or Gordon growth model, which states that If bond yields fall, all else being equal, the dividend yield should fall (and the price of equities rise). But if lower bond yields are matched by a change in long-term growth expectations, then there should be no positive impact on the current valuation from lower yields. Indeed, the uncertainty about future cash flows may increase the ERP, forcing the dividend yield up (or the price down). Fixed income assets, by contrast, provide a fixed nominal return over a defined period. The future returns are known in advance in nominal terms but not in real terms (because investors are not protected against surprises in future inflation). The ultimate return will depend on the current level of interest rates and a risk premium (an extra return) to compensate for the risk of default. The varying relationship between bonds and equities, which is affected by both the cycle and longer-term inflation expectations, can be viewed through the correlation between these two asset markets.


pages: 349 words: 104,796

Greed and Glory on Wall Street: The Fall of the House of Lehman by Ken Auletta

business climate, corporate governance, financial independence, fixed income, floating exchange rates, interest rate swap, New Journalism, profit motive, Ronald Reagan, Saturday Night Live, traveling salesman, zero-coupon bond

Although banking partners were not happy with the unwieldy, relatively inexperienced troika, to impose someone from trading on the forty-fourth-floor banking department—no matter how personally agreeable Shel Gordon was—made many bankers queasy. “Lew’s idea of breaking down the barrier between traders and bankers was for a trader to come up here,” says one longtime Lehman banker. Glucksman merged the equity division with the fixed-income division, which included all commercial paper and all trading in government securities. To manage the merged department, he elevated his thirty-seven-year-old protégé, Richard Fuld, who had been running fixed income alone. This move, in particular, made partners uneasy. Fuld was a man who, for all his abilities as a trader, was almost defiantly antisocial toward bankers; he avoided the partners’ dining room and complained openly about those “fucking bankers” who hogged Lehman’s shares. Some bankers referred to Fuld as “the gorilla,” in part because he spoke in monosyllabic grunts.

The tension between Glucksman and Peterson was hinted at by the fact that they were chauffeured uptown separately. Peterson rode to the lunch with J. Tomilson Hill III, a young Lehman banking partner he had helped to recruit; Glucksman rode with a member of his own team, Sheldon S. Gordon, head of equity trading and sales at Lehman, one of four major divisions at Lehman (the others being banking, fixed-income trading and investment management). “If I could avoid being with Peterson, I’d avoid being with Peterson,” explained Glucksman. “I couldn’t stand the monologues.” During cocktails, Glucksman and Peterson exchanged perfunctory greetings and mingled with the other seven guests at opposite ends of a bar area just outside the executive dining room. Glucksman began to seethe almost as soon as they entered the Hyde Room, a snug, cream-colored corner room dominated by a long, white-linen-covered dining table.

He became a partner in 1967, one of only a handful of nonbanking partners. He was placed in charge of all money market and trading activities in 1969, elevated to the board in 1971, and to the executive committee in 1972; by 1981 he was president and chief operating officer, and most Lehman managers reported to him. Glucksman’s rise coincided with the ascendancy of trading at Lehman and on Wall Street in general. In 1975 the fixed income and securities divisions at Lehman provided $18.5 million of Lehman’s pre-tax and pre-bonus profits; by 1983 this number had soared to $127.4 million. And by 1983, Lehman’s securities trading and distribution functions employed 1,863 people. Begun as an appendage to banking, by 1983 trading and distribution accounted for more than two-thirds of Lehman’s profits. The firm Glucksman joined included many talented individuals who liked to celebrate their “entrepreneurial spirit,” their ability to “get tough deals done.”


pages: 419 words: 130,627

Last Man Standing: The Ascent of Jamie Dimon and JPMorgan Chase by Duff McDonald

bank run, Blythe Masters, Bonfire of the Vanities, centralized clearinghouse, collateralized debt obligation, conceptual framework, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Exxon Valdez, financial innovation, fixed income, G4S, housing crisis, interest rate swap, Jeff Bezos, John Meriwether, Kickstarter, laissez-faire capitalism, Long Term Capital Management, margin call, market bubble, money market fund, moral hazard, negative equity, Nelson Mandela, Northern Rock, profit motive, Renaissance Technologies, risk/return, Rod Stewart played at Stephen Schwarzman birthday party, Saturday Night Live, sovereign wealth fund, statistical model, Steve Ballmer, Steve Jobs, technology bubble, The Chicago School, too big to fail, Vanguard fund, zero-coupon bond, zero-sum game

Salomon’s equity risk arbitrage unit suffered a loss of $100 million betting that British Telecommunications would purchase MCI Communications. Steve Black disbanded the group, but the firm’s much larger fixed income arbitrage group remained intact. Although the losses only intensified Dimon’s distaste for Maughan and the whole Salomon culture, the two men briefly found common cause, in a surprising situation. They combined to block another attempt at inappropriate nepotism by Weill. Just as Weill had argued in 1996 for his daughter’s advancement against Dimon’s wishes, in early 1998 he pushed to have his son Marc, then 41, placed in charge of the firm’s fixed income arbitrage group. Dimon and Maughan were united in their conviction that the division was a potential powder keg in the wrong hands—and that Marc Weill’s were definitely the wrong hands.

We lost more than $700 million, but it could have been multiples of that.” (Contrary to the image of Dimon as a perpetual cost-cutter, at the same time that he was reeling in the fixed income derivatives exposure, he was aggressively investing in building out Salomon Smith Barney’s equity derivatives business. According to Bob DiFazio, cohead of the company’s equities business, the business went from virtually zero revenues in the beginning of 1998 to a $400 million annual run rate shortly thereafter. Though Dimon wasn’t around to enjoy the fruits of his labor, the unit was up to a $1 billion run rate by late 1999.) The unwinding of the fixed income unit’s positions contributed to the market’s instability that summer, especially at Long-Term Capital Management (LTCM), which, having been founded by Salomon veterans, had on its books many of the same positions that Salomon was now vigorously selling.

But Jamie walked up to the board and changed a few things, and the next thing you know, the teacher said, ‘Oh my God, you’re right.’ It was a confidence with no fear.” Jay Light noticed the same thing that Mike Ingrisani had at Browning—Dimon had a powerful independent streak, and often a different grasp of what a manager’s priorities should be in case studies. He bore down on fundamental issues such as expense strategy and risk management. One day, in a class discussion of various fixed income investments, Light challenged Dimon on the concept of investing in a long-term zero coupon bond that nevertheless had a 15 percent yield-to-maturity. (In other words, although the bond offered no annual interest payments, it was selling at a price that would offer a 15 percent annualized return at maturity.) Dimon launched a bomb into the middle of class: “If you don’t see the merits of investing in a 15 percent zero coupon bond, Professor Light, then you probably shouldn’t be teaching this class.”


pages: 345 words: 87,745

The Power of Passive Investing: More Wealth With Less Work by Richard A. Ferri

asset allocation, backtesting, Bernie Madoff, buy and hold, capital asset pricing model, cognitive dissonance, correlation coefficient, Daniel Kahneman / Amos Tversky, diversification, diversified portfolio, endowment effect, estate planning, Eugene Fama: efficient market hypothesis, fixed income, implied volatility, index fund, intangible asset, Long Term Capital Management, money market fund, passive investing, Paul Samuelson, Ponzi scheme, prediction markets, random walk, Richard Thaler, risk tolerance, risk-adjusted returns, risk/return, Sharpe ratio, survivorship bias, too big to fail, transaction costs, Vanguard fund, yield curve, zero-sum game

Revisiting SPIVA Performance Studies Chapter 4 introduced the Standard & Poor’s Indices Versus Active (SPIVA) report. This study tracks one-, three-, and five-year active mutual fund performance across several different asset classes and is derived from a survivorship-bias-free database. The semiannual SPIVA report includes U.S. equity, U.S. real estate, U.S. fixed income, international equity, emerging markets equity, and international fixed income. The SPIVA report constantly reminds us that indexing has had remarkable success in all asset classes and style sectors over the years, albeit with varying results over different time periods. Over the long-term, index funds outperform the average active fund in every asset class, sector, and style. There are periods when active funds shine as a group, but they don’t shine by much and not for long.

Contents Foreword Preface Acknowledgments Part I: The Active Versus Passive Debate Chapter 1: Framing the Debate In the Beginning, There Were Active Funds Passive Investing Makes Its Case All about Indexes and Benchmarks The Portfolio Management Debate Summary Chapter 2: Early Performance Studies Cowles Commission Report The Quiet Period The Rise of Mutual Funds The Roaring 60s Summary Chapter 3: The Birth of Index Funds The First Indexed Portfolios The First Index Fund Summary Chapter 4: Advances in Fund Analysis The Early Years in Review Building on Success The Three Factor Model Three-Factor Analysis for Everyone Four-Factor Models and Beyond Does Anyone have Skill? Summary Chapter 5: Passive Choices Expand The Growth of Indexing The First Fixed Income Index Fund International Equity Index Funds Real Estate Investment Trusts U.S. Small Cap Revisiting SPIVA Performance Studies Active Management Invades Indexing Summary Chapter 6: Portfolios of Mutual Funds Efficient Portfolios Portfolio Choices The Bottom Line Is Your Bottom Line Summary Part II: Chasing Alpha and Changing Behavior Chapter 7: The Futility of Seeking Alpha All That’s Needed Is a Crystal Ball Past Performance as a Way to Predict Future Returns Fund Expenses as a Predictor of Top Performance Ratings as a Predictor of Top Performance Qualitative Factors as a Predictor of Top performance Summary Chapter 8: Active and Passive Asset Allocation Tactical Versus Strategic Mutual Fund Flows Show Bad Timing Measuring the Timing Gap Dumb Money versus Smart Money Putting It All Together Summary Chapter 9: Changing Investor Behavior Helping People Go Passive Three Non-Indexers Investing Is Serious Business Summary Part III: The Case for Passive Investing Chapter 10: The Passive Management Process The Five Step Process Investment Policy Statements Summary Chapter 11: The Passive Case for Individual Investors Begin at the End Estimating Future Obligations The Asset Side Matching Assets to Obligations Asset Allocation Risk!

The report compares active managers to their appropriate S&P style and size indices and tallies the number of winners and losers. It was an innovative idea that’s now widely read by investors and advisors, and results in interesting media commentary from believers in active investing and passive investing. The SPIVA scorecard compares the quarterly performance data of more than 3,500 actively managed mutual funds covering U.S. equities, international equities, and fixed income funds to their appropriate market benchmarks. The analysis includes size, style, and sector indices. This methodology is designed to provide an accurate and objective apples to apples comparison. The U.S. equity funds are segregated into 13 different categories including large cap, mid cap, and small cap indices. The groups are then benchmarked to the S&P 1500, S&P 500, S&P 400, and S&P 600 style indices and one real estate investment trust (REIT) benchmark.


pages: 374 words: 114,600

The Quants by Scott Patterson

Albert Einstein, asset allocation, automated trading system, beat the dealer, Benoit Mandelbrot, Bernie Madoff, Bernie Sanders, Black Swan, Black-Scholes formula, Blythe Masters, Bonfire of the Vanities, Brownian motion, buttonwood tree, buy and hold, buy low sell high, capital asset pricing model, centralized clearinghouse, Claude Shannon: information theory, cloud computing, collapse of Lehman Brothers, collateralized debt obligation, commoditize, computerized trading, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, Donald Trump, Doomsday Clock, Edward Thorp, Emanuel Derman, Eugene Fama: efficient market hypothesis, fixed income, Gordon Gekko, greed is good, Haight Ashbury, I will remember that I didn’t make the world, and it doesn’t satisfy my equations, index fund, invention of the telegraph, invisible hand, Isaac Newton, job automation, John Meriwether, John Nash: game theory, Kickstarter, law of one price, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, margin call, merger arbitrage, money market fund, Myron Scholes, NetJets, new economy, offshore financial centre, old-boy network, Paul Lévy, Paul Samuelson, Ponzi scheme, quantitative hedge fund, quantitative trading / quantitative finance, race to the bottom, random walk, Renaissance Technologies, risk-adjusted returns, Robert Mercer, Rod Stewart played at Stephen Schwarzman birthday party, Ronald Reagan, Sergey Aleynikov, short selling, South Sea Bubble, speech recognition, statistical arbitrage, The Chicago School, The Great Moderation, The Predators' Ball, too big to fail, transaction costs, value at risk, volatility smile, yield curve, éminence grise

At first Asness didn’t realize he’d made a profound discovery about hidden market patterns that he could exploit to make money. He was simply thrilled that he could write his dissertation and graduate. The money would come soon enough. In 1992, as Asness buckled down on his dissertation on momentum, he received an offer to work in the fixed-income group at Goldman Sachs. A small but growing division at Goldman, called Goldman Sachs Asset Management, was reaching out to bright young academics to build what would become one of the most formidable brain trusts on Wall Street. Asness’s first real job at Goldman was building fixed-income models and trading mortgage-backed securities. Meanwhile, he spent nights and weekends toiling away at his dissertation and thinking hard about a choice he’d have to make: whether to stay in academia or pursue riches on Wall Street. His decision was essentially made for him.

Meriwether and his merry band of quants had been so successful, first at Salomon Brothers and then at LTCM, that bond trading desks across Wall Street, from Goldman Sachs to Lehman Brothers to Bear Stearns, were doing their level best to imitate their strategies. That ultimately spelled doom for LTCM, known by many as Salomon North. The first blow was a mere mosquito bite that LTCM barely felt. Salomon Brothers’ fixed-income arbitrage desk had been ordered to shut down by its new masters, Travelers Group, which didn’t like the risk they were taking on. As Salomon began to unwind its positions—often the very same positions held by LTCM—Meriwether’s arbitrage trades started to sour. It set off a cascade as computer models at firms with similar positions, alerted to trouble, spat out more sell orders. By August 1998, the liquidation of relative-value trades across Wall Street had caused severe pain to LTCM’s positions.

Goldman had given Asness his start, shown faith in his abilities, and provided him the freedom to implement his ideas and hire his own people. It seemed like a betrayal. The more Asness thought about it, the more it seemed like a bad idea. Then he met a man with the ideal set of skills to help launch a hedge fund: David Kabiller. David Kabiller had been something of a wanderer among Goldman’s ranks since he’d joined the bank in a summer training program in 1986. He’d worked in fixed income, equities, and pension services. He first met Asness as a liaison between institutional investors and GSAM, which managed money for outside clients in addition to running proprietary funds for Goldman itself. Kabiller, who’s something of a mix between a Wall Street financier and car salesman, was quick to notice that Global Alpha was raking in money. Global Alpha had a live, second-by-second computerized tabulation of its profit and loss.


pages: 621 words: 123,678

Financial Freedom: A Proven Path to All the Money You Will Ever Need by Grant Sabatier

"side hustle", 8-hour work day, Airbnb, anti-work, asset allocation, bitcoin, buy and hold, cryptocurrency, diversified portfolio, Donald Trump, financial independence, fixed income, follow your passion, full employment, Home mortgage interest deduction, index fund, loss aversion, Lyft, money market fund, mortgage debt, mortgage tax deduction, passive income, remote working, ride hailing / ride sharing, risk tolerance, Skype, stocks for the long run, stocks for the long term, TaskRabbit, the rule of 72, time value of money, uber lyft, Vanguard fund

If you are going to need to withdraw money from your investments to cover your expenses, you’ll likely want to shift your investments to a more conservative stock/bond allocation so you can rely on bonds or some other type of fixed-income asset. A common asset allocation for early retirees is 60 percent stocks/40 percent bonds or 40 percent stocks/60 percent bonds. These allocations both allow you to participate in stock market growth over time but have fixed income from bonds that you can withdraw and live on. With a more conservative allocation, if you are living off fixed-income assets you can leave your stock investments alone and let them keep growing and compounding. Although other early retirees who can withdraw less than 3 to 4 percent of their portfolio to cover their monthly expenses leave their money in 100 percent stocks to maximize its long-term growth potential, it’s up to you to determine the level of risk you are willing to take and if you would prefer to live off fixed guaranteed income.

You can also minimize the sequence-of-returns risk with the right withdrawal strategy, which might include moving some of your investments into fixed income (bonds) that you can live off during your first five to ten years of retirement, while leaving the rest of your money in stocks to continue growing. This way you would guarantee income that’s not impacted by the performance of the stock market. You should try to live off cash and your fixed-income investments and supplement them with your stock market withdrawals; this way you are always keeping as much money growing in the stock market during both down years and up years. During the years when the stock market is down, you should live off your fixed income and cash, and when it’s up, you can live off your stock returns if you need more money. A 3 to 4 percent withdrawal rate is an extremely conservative withdrawal strategy, and as long as you are reasonable during your first five to ten years of retirement, after that period your investment portfolio could easily double, triple, or quadruple in size over the subsequent years, making it possible for you to easily increase your expenses and spend more money if you want.

On the other hand, Kristy and Bryce, who reached financial independence at thirty-one and thirty-two, respectively, and are now in their mid-thirties, are more conservative and have shifted their investments to 60 percent stocks and 40 percent bonds so they can get a fixed amount of pretty much guaranteed income. No matter what happens in the stock market, their investments are set up to generate between $30,000 and $40,000 in dividends and fixed income while maintaining their investment principal. They prefer the security over the growth potential, but since they do have 60 percent invested in stocks, they can still participate in the gains as the stock market goes up, just at a lower rate than Brandon or I do. J. P., who reached financial independence at twenty-eight, is also conservative, but not as much as Kristy and Bryce. She has about 70 percent of her portfolio in stocks and 30 percent in bonds/fixed income. On the facing page is a chart of asset allocation recommendations based on your age and years to retirement. While I still recommend you use years to retirement as the guide, I’ve also included baseline age asset allocation recommendations since they are a good reference point if you are just starting out.


pages: 272 words: 19,172

Hedge Fund Market Wizards by Jack D. Schwager

asset-backed security, backtesting, banking crisis, barriers to entry, beat the dealer, Bernie Madoff, Black-Scholes formula, British Empire, business cycle, buy and hold, Claude Shannon: information theory, cloud computing, collateralized debt obligation, commodity trading advisor, computerized trading, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, delta neutral, diversification, diversified portfolio, Edward Thorp, family office, financial independence, fixed income, Flash crash, hindsight bias, implied volatility, index fund, intangible asset, James Dyson, Jones Act, Long Term Capital Management, margin call, market bubble, market fundamentalism, merger arbitrage, money market fund, oil shock, pattern recognition, pets.com, Ponzi scheme, private sector deleveraging, quantitative easing, quantitative trading / quantitative finance, Right to Buy, risk tolerance, risk-adjusted returns, risk/return, riskless arbitrage, Rubik’s Cube, Sharpe ratio, short selling, statistical arbitrage, Steve Jobs, systematic trading, technology bubble, transaction costs, value at risk, yield curve

I thought that economic conditions couldn’t get any better. 5 Anyone who had a pulse had a job, equity markets were at their highs, and yet we were not generating any inflation. If we were not generating inflation under those conditions, then what would happen if we started to slow at the margins? I was so focused on the long fixed-income trade that for the first three or four years of the fund, probably two-thirds of the trades were in fixed-income. Was it the topping of the equity market in early 2000 that got you long in fixed-income? The break in equities was definitely the catalyst for the fixed-income trade, but the trade was going to happen anyway. I use the fundamentals to have a directional bias, and I use the technicals to confirm that bias. Once I had the catalyst, I could say that yields should never again see their previous high. I could then decide what I was willing to risk, and let the market work.

We watched the markets very carefully, and in early 2008, I transferred a vast proportion of the firm’s money into two-year treasury notes. I got rid of all the money market funds. I put all the traders into a wind down of counterparty exposure. We dumped outright exposure to every bank possible and went maximum long fixed income. The systematic trend-following strategy was consistently moving into a similar position. It started reversing from long to short in equities and commodities and going hugely long in fixed income. Again, it was all the same trade, wasn’t it? So when the market meltdown hit later in 2008, you were positioned perfectly. In 2008, BlueCrest made the most amount of money for its investors in its history up to that point. Even though we were making loads of money, many of our investors redeemed simply because they couldn’t get their cash from anyone else.

Does that imply that you didn’t trade the Nasdaq from the short side even after you were sure the bull market was dead? No, I didn’t because the repercussions of the top were a lot easier to play than being short the Nasdaq itself. You had a broad bubble in assets. The U.S. economy had been built up by a massive mispricing of assets. Once the Nasdaq burst and everything unraveled, it was clear the economy would slow down. The economic downturn led to a big move in fixed income that provided a much calmer way to play that idea than a direct trade in equities. So rather than consider the short side of the Nasdaq, you traded the long side of the bonds. That’s right. Are there any current examples of markets that are in euphoria-driven states that are running counter to fundamentals? I wouldn’t say they are counter to the fundamentals, but rather that they are overpricing one particular outcome.


The Trade Lifecycle: Behind the Scenes of the Trading Process (The Wiley Finance Series) by Robert P. Baker

asset-backed security, bank run, banking crisis, Basel III, Black-Scholes formula, Brownian motion, business continuity plan, business process, collapse of Lehman Brothers, corporate governance, credit crunch, Credit Default Swap, diversification, fixed income, hiring and firing, implied volatility, interest rate derivative, interest rate swap, locking in a profit, London Interbank Offered Rate, margin call, market clearing, millennium bug, place-making, prediction markets, short selling, statistical model, stochastic process, the market place, the payments system, time value of money, too big to fail, transaction costs, value at risk, Wiener process, yield curve, zero-coupon bond

However, for large capital amounts it is highly unlikely that a single bank would have the funds and the desire to lend by itself. To overcome this problem, companies issue bonds. Purchasers of bonds pay capital to the company, which is repaid to them at the end of the period (term) of the bond. The lenders are rewarded by receiving interest in the form of coupons, in most cases throughout the term of the bond. Fixed income is another name for the asset class comprising of bonds. The term fixed income is used because, once a bond is issued, the expected income is known. This contrasts with equities, where dividend payments are unknown. Another difference with equities is that bonds have a termination date. A further distinction is that many bonds are issued by governments wishing to raise finance, whereas all equities are corporate. Sovereign debt Government bonds are known as sovereigns.

So the underlying process is the same but the asset classes are different. The same is true for financial products. Buying shares is intrinsically the same as buying aluminium, sovereign bonds or purchasing dollars in exchange for euros. However, since the people and trading environments of each of these trades are very different, we generally group them into different asset classes. (The examples above corresponding to equities, commodity, fixed income and foreign exchange (FX)). The processes for dealing with each of these trades will normally depend on the asset class rather than the product itself. As we have seen, some products exist in more than one asset class. Every asset class has a suite of possible products. A financial institution organises its traders, sales staff, middle office and controllers around each asset class rather than around each product.

However, everything is committed at the time of transaction and the size of payment and assets is fully determined and cannot be changed. Examples of spot trades in various asset classes are: Commodity: We buy 1m troy ounces of Gold from Commerzbank at USD 1000 per troy ounce. Equity: We buy 10,000 Ford Motor Company shares from BNP Paribas at USD 17.32 per share. FX: We buy 10m Swiss Francs from RBS at exchange rate of 1.118142 francs per US dollar. Fixed income: We buy 5m IBM Bonds from Chase Manhattan at 92.88 cents per bond. Note that when purchasing an equity or a bond, we have settled outright with the counterparty (BNP Paribas or Chase Manhattan in the examples above) so they have no further financial responsibility or liability, but we now own an active financial instrument and will need to manage it in order to draw dividends or coupons in the future from the issuer (Ford Motor Company or IBM respectively).


pages: 566 words: 155,428

After the Music Stopped: The Financial Crisis, the Response, and the Work Ahead by Alan S. Blinder

"Robert Solow", Affordable Care Act / Obamacare, asset-backed security, bank run, banking crisis, banks create money, break the buck, Carmen Reinhart, central bank independence, collapse of Lehman Brothers, collateralized debt obligation, conceptual framework, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, Detroit bankruptcy, diversification, double entry bookkeeping, eurozone crisis, facts on the ground, financial innovation, fixed income, friendly fire, full employment, hiring and firing, housing crisis, Hyman Minsky, illegal immigration, inflation targeting, interest rate swap, Isaac Newton, Kenneth Rogoff, liquidity trap, London Interbank Offered Rate, Long Term Capital Management, market bubble, market clearing, market fundamentalism, McMansion, money market fund, moral hazard, naked short selling, new economy, Nick Leeson, Northern Rock, Occupy movement, offshore financial centre, price mechanism, quantitative easing, Ralph Waldo Emerson, Robert Shiller, Robert Shiller, Ronald Reagan, shareholder value, short selling, South Sea Bubble, statistical model, the payments system, time value of money, too big to fail, working-age population, yield curve, Yogi Berra

There was also a gigantic bond bubble that you may never have heard of. Bonds and other fixed-income securities derive their names from the fact that the borrower is legally obliged to pay the lender a fixed number of dollars (or euros, or pounds, or whatever) at dates set in advance. Should the borrowing company fare exceptionally well during the decade, the lender will not share in its prosperity—it will just receive the promised interest payments. Similarly, if the business does poorly, the lender will not share in the downside—unless the borrower defaults. This fixity of the income stream contrasts starkly with common stocks, where dividends and capital gains rise and fall with the fortunes of companies and are not specified in advance. The fundamental value of a fixed-income security is easy to compute in the absence of default risk: One need compute only the present values of all the future flows of interest and principal, which are fixed and known—and then add them up.

The bubble in house prices had as its counterpart a bubble in MBS because investors falsely believed that the probabilities of mortgage default were tiny. Just as the fundamentals for, say, stocks and houses are often improving as a bubble inflates, the same is true of bonds and other fixed-income securities. During prosperous times, default rates drop to very low levels. Investors then deduce that rational interest-rate spreads over Treasuries—just enough to compensate lenders for the default risks they bear—should also drop to very low levels. The trouble is, how low is low? Markets sometimes get carried away. DEFAULT RISK AND INTEREST-RATE SPREADS One key respect in which fixed-income securities differ is their risk of default. There is no such risk on U.S. government securities. Dating back to fundamental decisions made by Alexander Hamilton, the nation’s first secretary of the Treasury, the U.S. government has always paid its debts in full and on time.

Investors should never have extrapolated the amazingly favorable default experience of 2004–2006 into the indefinite future. But they did. It was the kind of thinking that led to the bond-market bubble. As investors shifted out of Treasuries into riskier fixed-income securities—whether Columbian government bonds or MBS backed by subprime mortgages—those riskier securities were bid up in price, and hence down in yield. You had to pay more to buy the same stream of interest payments. So what was once, say, a 150-basis-point reward for bearing more risk became a 100-basis-point reward, or maybe just a 50-basis-point reward. Investors’ response to dwindling yields on fixed-income securities was to try to magnify their yields by going for more leverage—which is the second item on my list of villains. If bearing a little additional risk would bring you only, say, 50 basis points in additional return, you could magnify that reward to 500 basis points by making the investment with 10-to-1 leverage.


pages: 265 words: 93,231

The Big Short: Inside the Doomsday Machine by Michael Lewis

Asperger Syndrome, asset-backed security, collateralized debt obligation, Credit Default Swap, credit default swaps / collateralized debt obligations, diversified portfolio, facts on the ground, financial innovation, fixed income, forensic accounting, Gordon Gekko, high net worth, housing crisis, illegal immigration, income inequality, index fund, interest rate swap, John Meriwether, London Interbank Offered Rate, Long Term Capital Management, medical residency, money market fund, moral hazard, mortgage debt, pets.com, Ponzi scheme, Potemkin village, quantitative trading / quantitative finance, Robert Bork, short selling, Silicon Valley, the new new thing, too big to fail, value at risk, Vanguard fund, zero-sum game

said Danny Moses. The short answer to that second question was: the optimists. The subprime mortgage market in its current incarnation never had done anything but rise. The people in it who were regarded as successes were those who had always said "buy." Now they should really all be saying "sell," but they didn't know how to do it. "You always knew that fixed income guys thought they knew more than you did," said Eisman, "and generally that was true. I wasn't a fixed income guy, but here I'd taken this position that was a bet against their whole industry, and I wanted to know if they know something I don't. Could it really be this obvious? Could it really be this simple?" He entered private meetings with the lenders and the bankers and the rating agencies probing for an intelligence he had yet to detect. "He was in learning mode," said Vinny.

By 2005, 75 percent of subprime loans were some form of floating-rate, usually fixed for the first two years. The original cast of subprime financiers had been sunk by the small fraction of the loans they made that they had kept on their books. The market might have learned a simple lesson: Don't make loans to people who can't repay them. Instead it learned a complicated one: You can keep on making these loans, just don't keep them on your books. Make the loans, then sell them off to the fixed income departments of big Wall Street investment banks, which will in turn package them into bonds and sell them to investors. Long Beach Savings was the first existing bank to adopt what was called the "originate and sell" model. This proved such a hit--Wall Street would buy your loans, even if you would not!--that a new company, called B&C mortgage, was founded to do nothing but originate and sell.

In the fog of the first eighteen months of running his own business, Eisman had an epiphany, an identifiable moment when he realized he'd been missing something obvious. Here he was, trying to figure out which stocks to pick, but the fate of the stocks depended increasingly on the bonds. As the subprime mortgage market grew, every financial company was, one way or another, exposed to it. "The fixed income world dwarfs the equity world," he said. "The equity world is like a fucking zit compared to the bond market." Just about every major Wall Street investment bank was effectively run by its bond departments. In most cases--Dick Fuld at Lehman Brothers, John Mack at Morgan Stanley, Jimmy Cayne at Bear Stearns--the CEO was a former bond guy. Ever since the 1980s, when the leading bond firm, Salomon Brothers, had made so much money that it looked as if it was in a different industry than the other firms, the bond market had been where the big money was made.


pages: 413 words: 117,782

What Happened to Goldman Sachs: An Insider's Story of Organizational Drift and Its Unintended Consequences by Steven G. Mandis

activist fund / activist shareholder / activist investor, algorithmic trading, Berlin Wall, bonus culture, BRICs, business process, buy and hold, collapse of Lehman Brothers, collateralized debt obligation, commoditize, complexity theory, corporate governance, corporate raider, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, disintermediation, diversification, Emanuel Derman, financial innovation, fixed income, friendly fire, Goldman Sachs: Vampire Squid, high net worth, housing crisis, London Whale, Long Term Capital Management, merger arbitrage, Myron Scholes, new economy, passive investing, performance metric, risk tolerance, Ronald Reagan, Saturday Night Live, Satyajit Das, shareholder value, short selling, sovereign wealth fund, The Nature of the Firm, too big to fail, value at risk

Also, I worked with the principal investment area (PIA makes investments in or buys control of companies with money collectively from clients, Goldman, and employees). Then I returned to M&A, rising to the head of the hostile raid defense business (defending a company from unsolicited take-overs—one of the cornerstones of Goldman’s M&A brand and reputation) and becoming business unit manager of the M&A department. Finally, I ended up as a proprietary trader and ultimately portfolio manager in the fixed income, commodities, and currencies division (FICC)—similar to an internal hedge fund—managing Goldman’s own money. My rotations to a different geographic region and through different divisions were typical at the time for a certain percentage of selected employees in order to train people and unite the firm. Throughout my career at Goldman, I served on firm-wide and divisional committees, dealing with important strategic and business process issues.

The resignations caused people to think more about themselves, their own interests, and their own personal ambitions—and materialism began to grow.16 With Friedman’s sudden resignation and no succession plan, a fierce power struggle ensued, increasing the instability and prompting personal reflection. Corzine, a trader in the FICC department who also had a CFO-type role (which at the time was typically the head of fixed income and chief risk allocator), aggressively announced to the management committee that he wanted to be senior partner (and be given the title of CEO) and for Paulson to be the number two, with the title of COO. In recent memory there had always been co-head senior partners, reflecting a culture of teamwork. There were “the two Johns” and then “Steve and Bob.” Many divisions and departments had co-heads.

To put this into context, he estimated the impact at 27 percent, 9 percent, and 8 percent of total consolidated revenues of Morgan Stanley, Bank of America, and J.P. Morgan, respectively. Certain Goldman client-oriented sales and trading desks had “proprietary trading” operations. They got to see client order flow, but theoretically they existed to provide liquidity or “facilitate client trades.” This was prevalent in less liquid, more opaque products and desks, especially fixed-income securities like high-yield bonds, where it may not have been easy to immediately match a buyer and a seller. It was also prevalent in relatively lightly regulated markets such as foreign exchange. Generally, proprietary trading on client-oriented sales and trading desks was less frequent in highly transparent and highly regulated areas such as equities. Merchant Banking and Private Equity Become a Larger Percentage of Revenues GS Capital Partners was started in 1992 with about $1 billion in assets and grew to $1.75 billion by 1995 and $2.75 billion by 1998.


pages: 311 words: 99,699

Fool's Gold: How the Bold Dream of a Small Tribe at J.P. Morgan Was Corrupted by Wall Street Greed and Unleashed a Catastrophe by Gillian Tett

accounting loophole / creative accounting, asset-backed security, bank run, banking crisis, Black-Scholes formula, Blythe Masters, break the buck, Bretton Woods, business climate, business cycle, buy and hold, collateralized debt obligation, commoditize, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, easy for humans, difficult for computers, financial innovation, fixed income, housing crisis, interest rate derivative, interest rate swap, Kickstarter, locking in a profit, Long Term Capital Management, McMansion, money market fund, mortgage debt, North Sea oil, Northern Rock, Renaissance Technologies, risk tolerance, Robert Shiller, Robert Shiller, Satyajit Das, short selling, sovereign wealth fund, statistical model, The Great Moderation, too big to fail, value at risk, yield curve

This started life in the summer of 2005, under the name of Dillon Read Capital Management. Second, in the autumn of 2005, the bank implemented a major review of its fixed-income business, hiring consultants from McKinsey and Oliver Wyman. On the advice of this review, the bank’s senior management decided to expand the securitization business. On paper, UBS did not seem well placed to make the move. Though the bank’s asset management group had already been investing in American mortgage products for several years, it did not have its own mortgage-lending operation. To make matters worse, when Costas created the new hedge fund, he took 120 of the bank’s staff with him, including many of the firm’s fixed-income specialists. However, that did not deter UBS’s senior management. The bank hired new traders in London and New York and told them to build a CDO business as fast as possible.

Morgan, the AAA rating assured them that the bank would always be around to fulfill its side of those deals. As business boomed, the swaps department basked in the knowledge that it was producing an ever-increasing share of the bank’s profits. By the early 1990s, it accounted for almost half the bank’s trading revenues, and Hancock had been promoted to run not just the derivatives group but also the entire department it was part of, known as fixed income. He was considered a prime candidate for CEO. A few months before the Boca off-site, a reporter from Fortune asked Hancock to explain how a complicated swap might work, and his response reaffirmed for her that derivatives traders were “like the spacecraft Galileo, heading for planet Jupiter.” “It would be something,” Hancock apparently said, “in which you get beyond binary risk and into a combination of risks, such as interest rates and currencies.

“Sandy” Warner, who had replaced Weatherstone in 1995, to take some decisive action to improve the bank’s profits. It was becoming increasingly clear—just as Hancock and Demchak had long complained—that the bank’s level of profitability was lagging behind its rivals’, and these losses were a body blow. Warner decided to throw his weight behind the value of credit derivatives business. He gave Hancock responsibility for managing not just the fixed-income business, but the commercial lending department, too. That was a radical move for staid J.P. Morgan, since almost no other Western bank had ever tried to combine lending, bonds, and derivatives into a single group before. Then Hancock handed responsibility for managing the loan book to Demchak. The Prince of Darkness was now in charge and able to remold the bank’s credit risk in line with all his dreams.


The Global Money Markets by Frank J. Fabozzi, Steven V. Mann, Moorad Choudhry

asset allocation, asset-backed security, bank run, Bretton Woods, buy and hold, collateralized debt obligation, credit crunch, discounted cash flows, discrete time, disintermediation, fixed income, high net worth, intangible asset, interest rate derivative, interest rate swap, large denomination, locking in a profit, London Interbank Offered Rate, Long Term Capital Management, margin call, market fundamentalism, money market fund, moral hazard, mortgage debt, paper trading, Right to Buy, short selling, stocks for the long run, time value of money, value at risk, Y2K, yield curve, zero-coupon bond, zero-sum game

The Global money markets THE FRANK J. FABOZZI SERIES Fixed Income Securities, Second Edition by Frank J. Fabozzi Focus on Value: A Corporate and Investor Guide to Wealth Creation by James L. Grant and James A. Abate Handbook of Global Fixed Income Calculations by Dragomir Krgin Managing a Corporate Bond Portfolio by Leland E. Crabbe and Frank J. Fabozzi Real Options and Option-Embedded Securities by William T. Moore Capital Budgeting: Theory and Practice by Pamela P. Peterson and Frank J. Fabozzi The Exchange-Traded Funds Manual by Gary L. Gastineau Professional Perspectives on Fixed Income Portfolio Management, Volume 3 edited by Frank J. Fabozzi Investing in Emerging Fixed Income Markets edited by Frank J. Fabozzi and Efstathia Pilarinu Handbook of Alternative Assets by Mark J. P. Anson The Exchange-Traded Funds Manual by Gary L.

See Long-Term Capital Management Statistical Release H.15, 35 tightening cycle, 42 320 Federal Reserve Bank of New York, 53 data collection, 68–69 Federal Reserve Banks, 28, 90 Federal Reserve Board, time deposits data series, 86 FGIC, 181 Finance companies, 2 Financial asset, 85 Financial information vendors, 69 Financial institutions, 2–4, 150, 161, 256, 258 debt obligations, 85 Financial market culture, differences, 3 Financial/global crises, 36 Financing rate, 113 First Chicago, 102 First Chicago NBD Corp., 102 First lien. See Properties Fitzgerald Securities, Inc., 34 Fix rate, 113 Fixed coupon bond, 234 Fixed-floating currency swap, 263 Fixed-income investments, 46 Fixed-income markets, 8 Fixed-rate assets, 283 Fixed-rate bond, 233 class, 161 Fixed-rate cash flow, 267 Fixed-rate closed-end HELs, 198 Fixed-rate debt, 82 market, 256 Fixed-rate gap, 293 Fixed-rate investors, 258 Fixed-rate issue, 105 Fixed-rate level-payment fully amortized mortgage, 152– 153, 158 Fixed-rate markets, 254 Fixed-rate payer, 230–232, 235– 238 benefits, 248 Fixed-rate payments, 236–237, 246–247.

Grieves, Mann, Marcus, and Ramanlal examine the performance of the riding strategy during this period and find that the overall performance of riding the yield curve deteriorates considerably. TREASURY BILLS WITH SPECIAL VALUE There is a substantial body of empirical evidence that suggests that certain Treasury bills have special value in addition to the value attributable to their cash flows.18 This additional value is present in bills whose maturity dates immediately precede calendar dates when corporate treasurers 18 See, for example, Kenneth D. Garbade, Fixed Income Analytics (Cambridge, MA: MIT Press, 1996) and Joseph P. Ogden, “The End of the Month as a Preferred Habitat: A Test of Operational Efficiency in the Money Market,” Journal of Financial and Quantitative Analysis (September 1987), pp. 329-343. U.S. Treasury Bills 43 require cash to make payments. Two prominent examples are quarter-end bills and tax bills. Quarter-end bills mature immediately prior to the end of the quarter.


pages: 354 words: 118,970

Transaction Man: The Rise of the Deal and the Decline of the American Dream by Nicholas Lemann

Affordable Care Act / Obamacare, Airbnb, airline deregulation, Albert Einstein, augmented reality, basic income, Bernie Sanders, Black-Scholes formula, buy and hold, capital controls, computerized trading, corporate governance, cryptocurrency, Daniel Kahneman / Amos Tversky, dematerialisation, diversified portfolio, Donald Trump, Elon Musk, Eugene Fama: efficient market hypothesis, financial deregulation, financial innovation, fixed income, future of work, George Akerlof, gig economy, Henry Ford's grandson gave labor union leader Walter Reuther a tour of the company’s new, automated factory…, index fund, information asymmetry, invisible hand, Irwin Jacobs, Joi Ito, Joseph Schumpeter, Kenneth Arrow, Kickstarter, life extension, Long Term Capital Management, Mark Zuckerberg, mass immigration, means of production, Metcalfe’s law, money market fund, Mont Pelerin Society, moral hazard, Myron Scholes, new economy, Norman Mailer, obamacare, Paul Samuelson, Peter Thiel, price mechanism, principal–agent problem, profit maximization, quantitative trading / quantitative finance, Ralph Nader, Richard Thaler, road to serfdom, Robert Bork, Robert Metcalfe, rolodex, Ronald Coase, Ronald Reagan, Sand Hill Road, shareholder value, short selling, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Social Responsibility of Business Is to Increase Its Profits, Steve Jobs, TaskRabbit, The Nature of the Firm, the payments system, Thomas Kuhn: the structure of scientific revolutions, Thorstein Veblen, too big to fail, transaction costs, universal basic income, War on Poverty, white flight, working poor

The price isn’t public; it’s set through a rapid private negotiation—as in, Do you want it at fifty-three dollars, or not? You’ve got five seconds. This kind of trading could go on continuously, every hour of every day. Morgan Stanley set up a fixed-income department, headed by John Mack, an extroverted bond salesman from a small town in North Carolina. Mack was a protégé of Dick Fisher’s—his department operated on the trading floor that Fisher had set up—and was another member of the restless, younger, nontraditional generation at Morgan Stanley. His family had originally come from Lebanon and had worked as shopkeepers; Mack himself was exuberantly theatrical and incautious, preoccupied with keeping large blocks of securities moving smartly on and off the floor. Because fixed-income trading did not take place on public exchanges, the Morgan Stanley traders knew more than their buyers or the sellers about prices.

The firm’s job was not to make sure both parties were getting a fair price; it was to match buyers (who thought the sellers were underpricing) with sellers (who thought the buyers were overpaying). Fixed-income was another division that required the firm to buy large quantities of financial instruments, at least temporarily, either with its own capital—or, increasingly, with borrowed money. When Morgan Stanley itself was the buyer or the seller, its job was to take advantage of the party on the other side of the transaction. If, as the traders liked to say, you could rip their face off, tear their eyes out, blow them up, or whatever cock-of-the-walk metaphor was in favor that day, that meant you were doing your job. Before long, fixed-income was producing far more trading volume than stocks, at Morgan Stanley and in the markets generally. The older partners who objected to these new activities were, it’s true, stolidly conservative, but they weren’t wrong to worry about what was happening to the firm.

So he decided to have a career in his family’s tradition, but in an untraditional way, seizing every opportunity to be aggressive in the mold of the unrestrained capitalists of the Gilded Age. He talked rapidly, joked, cajoled, prodded, trying to get the firm moving faster. His operation at Morgan Stanley required a sales force, which Morgan Stanley hadn’t had, and more trading capacity and additional capital. “Fixed income” is a Wall Street term that covers instruments that pay investors at a set rate—for example, a ten-year government bond that can be redeemed at the end of that time for the amount it cost, plus interest. The name connotes cautious, buy-and-hold investors, but as time went on, what it came to mean was almost completely different. Stocks are bought and sold on public exchanges, so their price at every moment is a matter of record.


pages: 130 words: 11,880

Optimization Methods in Finance by Gerard Cornuejols, Reha Tutuncu

asset allocation, call centre, constrained optimization, correlation coefficient, diversification, finite state, fixed income, frictionless, frictionless market, index fund, linear programming, Long Term Capital Management, passive investing, Sharpe ratio, transaction costs, value at risk

We apply the robust optimization approach discussed in the previous section to an asset allocation problem. We consider a universe of 5 asset classes: large cap growth stocks, large cap value stocks, small cap growth stocks, small cap value stocks, and fixed income securities. To represent each asset class, we use a monthly log-return time series of corresponding market indices: Russell 1000 growth and value indices for large cap stocks, Russell 2000 growth and value indices for small cap stocks, and Lehman Brothers US Intermediate Government/Credit Bond index for fixed income securities. Lehman Brothers U.S. Intermediate Government/Credit Bond Index is an unmanaged index generally representative of government and investment-grade corporate securities with maturities of 1-10 years. Our time series data spans the period January 1978 (the inception date of Russell indices) to July 2002, a total of n = 283 months.

SOLUTION ROBUSTNESS 91 Using the data presented above, we generated the standard and robust efficient frontiers. Figure 7.1 depicts the standard efficient frontier obtained by using the 50 percentile values for expected returns and covariances as inputs and the composition of the portfolios on the efficient frontier. Lowest risk efficient portfolios are obtained, as expected, using the fixed income securities. As one moves along the efficient frontier toward the efficient portfolio with the highest expected return, fixed income securities are gradually replaced by a mixture of large-cap and small-cap value stocks. Close to the high-return end of the frontier, large-cap stocks are also phased out and one gets a portfolio consisting entirely of small cap value stocks. Efficient frontier with nominal data Composition of efficient portfolios using nominal data 100 90 14 Cumulative percentages in different asset classes Expected return of efficient portfolios (annualized percentages) 15 13 12 11 80 Russell 1000 Value Russell 2000 Value LB IT Gov/Cre 70 60 50 40 30 20 10 10 9 4 6 8 10 12 14 16 Standard deviation of efficient portfolios (annualized percentages) 18 0 9.5 10 10.5 11 11.5 12 12.5 13 Expected return of efficient portfolios (annualized percentages) 13.5 14 Figure 7.1: The efficient frontier and the composition of the efficient portfolios found using the classical MVO approach without any consideration of input uncertainty.

If λR = 0, show that xR is an optimal solution to (5.16). (Hint: What are the optimality conditions for (5.16)? How are they related to (5.2)?) 2. Implement the returns-based style analysis approach to determine the effective asset mix of your favorite mutual fund. Use the following asset classes as your “factors”: Large growth stocks, large value stocks, small growth stocks, small value stocks, international stocks, and fixed income investments. You should obtain time series of returns representing these asset classes from on-line resources. You should also obtain a corresponding time series of returns for the mutual fund you picked for this exercise. Solve the problem using 30 periods of data (i.e., T = 30). 3. Classification problems are among the important classes of problems in financial mathematics that can be solved using optimization models and techniques.


pages: 225 words: 11,355

Financial Market Meltdown: Everything You Need to Know to Understand and Survive the Global Credit Crisis by Kevin Mellyn

asset-backed security, bank run, banking crisis, Bernie Madoff, bonus culture, Bretton Woods, business cycle, collateralized debt obligation, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, cuban missile crisis, disintermediation, diversification, fiat currency, financial deregulation, financial innovation, financial intermediation, fixed income, Francis Fukuyama: the end of history, George Santayana, global reserve currency, Home mortgage interest deduction, Isaac Newton, joint-stock company, Kickstarter, liquidity trap, London Interbank Offered Rate, long peace, margin call, market clearing, mass immigration, money market fund, moral hazard, mortgage tax deduction, Northern Rock, offshore financial centre, paradox of thrift, pattern recognition, pension reform, pets.com, plutocrats, Plutocrats, Ponzi scheme, profit maximization, pushing on a string, reserve currency, risk tolerance, risk-adjusted returns, road to serfdom, Ronald Reagan, shareholder value, Silicon Valley, South Sea Bubble, statistical model, The Great Moderation, the new new thing, the payments system, too big to fail, value at risk, very high income, War on Poverty, Y2K, yield curve

The earliest bonds were sold by governments to finance wars, which are by nature fairly short but very expensive. The buyer of a bond has a need for future income and is willing to put up money for it today. So the bond buyer is really buying a series of fixed interest payments that The Financial Market Made Simple might continue for many years, and even in a few cases forever. That is why investment bankers call the bond business ‘‘fixed income.’’ The rate of interest is often referred to as the ‘‘coupon,’’ referring to the time when bonds were printed with paper coupons that had to be cut out and presented to the bond issuers when each interest payment fell due. That is why the idle rich are still sometimes referred to as ‘‘coupon clippers.’’ Bonds and Risk Unless the bond issuer stops paying the coupon—in financespeak, the issuer ‘‘defaults’’—bonds are a dull, steady source of income.

In reality, company insiders almost always capture the lion’s share of any new stock issue. However, great fortunes have been amassed by canny investors like Warren Buffett in the equity markets of the world. Such investors are a kind of celebrity in some circles. Both the upside and the downside of equity investing are pretty much unbounded. Stocks offer real excitement and feed our dreams of riches. They are a bet on the future. Bonds by contrast offer ‘‘fixed income.’’ Stocks versus Bonds That contrast is why, in the short run, the prices for stocks and bonds tend to move in opposite directions. Markets are always in flux between fear and greed. When people are optimistic about the future prospects of the economy, fear takes a back seat. Stock markets become convinced that the prices of almost all shares can only go higher. In such bull markets—and we are just coming off the longest bull market for corporate equities in history, going all the way back to Ronald Reagan’s first term, with only a few brief interruptions— everyone believes that they can always make more money in stocks than in bonds.

From this, you might conclude they represent a fundamentally better ‘‘asset class’’ for growing your money. What you are not told is that over that period most of the total growth in the value of stock market took place on a handful of days. Most of the losses took place in a few days during sudden panics and sell-offs. The averages over a century tell you almost nothing. If you missed the upswings and were caught in a big downdraft, you would have done better in fixed income. The point is that all financial instruments involve risk/reward tradeoffs. There are no safe bets that have big upsides. Because the risk/reward tradeoffs of stocks and bonds are never ideal for either issuers or investors, the markets have over the years developed ‘‘hybrid’’ classes of financial instruments that are neither debt nor equity instruments. These are mainly used to tap the money of big institutional investors.


pages: 339 words: 109,331

The Clash of the Cultures by John C. Bogle

asset allocation, buy and hold, collateralized debt obligation, commoditize, corporate governance, corporate social responsibility, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, diversified portfolio, estate planning, Eugene Fama: efficient market hypothesis, financial innovation, financial intermediation, fixed income, Flash crash, Hyman Minsky, income inequality, index fund, interest rate swap, invention of the wheel, market bubble, market clearing, money market fund, mortgage debt, new economy, Occupy movement, passive investing, Paul Samuelson, Ponzi scheme, post-work, principal–agent problem, profit motive, random walk, rent-seeking, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Shiller, shareholder value, short selling, South Sea Bubble, statistical arbitrage, survivorship bias, The Wealth of Nations by Adam Smith, transaction costs, Vanguard fund, William of Occam, zero-sum game

Perhaps even more significantly, bond index funds as a group now claim a record high 17 percent market share among taxable bond funds—$370 billion of the $2.4 trillion total. What’s more, during 2011, bond index funds accounted for fully 40 percent of the investor cash flow into taxable fixed-income funds as a group. This penetration is a harbinger that the trend toward bond indexing will continue to strengthen, just as has the trend toward stock indexing. This accelerating trend confirms what Peter Fisher, talented head of the fixed-income group for giant global money manager BlackRock, has observed: “We’re moving to the second phase of the index revolution. The world is a frightening, uncertain place, and investors want to make their (bond) portfolios much simpler so they can sleep at night.” With an annual expense ratio now averaging 0.10 percent (10 basis points), Vanguard Total Bond Market Index Fund remains a ferocious competitor.

And they were more than ably supported by Wellington’s bond managers, who maintained a fixed-income portfolio for which investment-grade quality continued to be the watchword. Paul Sullivan led these professionals during 1972–1995, ably succeeded by Paul Kaplan, and then by John Keogh. The bond managers also share in the credit for the Fund’s renaissance. Wellington’s portfolio managers continue to reaffirm the merit of the strategy adopted by the Fund’s Board back in 1978. Here’s what they wrote to the Fund’s shareholders in the 2000 Annual Report A reasonable level of current income and long-term growth in capital can be achieved without undue risk by holding 60% to 70% of assets in equities and the balance in fixed income securities. Consistent with this approach, dividend-paying stocks dominate the fund’s equity segment.

I have my doubts, and so far the facts seem to back me up. The good news is that many of the new funds were bond funds and money market funds, which for decades have provided generous premium yields over stocks and also over traditional bank savings accounts, where yields were constrained by federal government regulation until 1980. Today, of course, these generous yields have disappeared. But these new “fixed-income” funds provided more stable portfolio values and offered access to sectors of the financial market not previously available to most families. The bad news is that in the equity fund sector of the industry, the massive proliferation of so many untested strategies (and often untested managers) resulted in confusion for investors. The rise of such proliferation and the seemingly infinite choices available seemed to imply that achieving earnings on investment returns that exceeded those of the stodgy stock market were easy.


pages: 403 words: 119,206

Toward Rational Exuberance: The Evolution of the Modern Stock Market by B. Mark Smith

bank run, banking crisis, business climate, business cycle, buy and hold, capital asset pricing model, compound rate of return, computerized trading, credit crunch, cuban missile crisis, discounted cash flows, diversified portfolio, Donald Trump, Eugene Fama: efficient market hypothesis, financial independence, financial innovation, fixed income, full employment, income inequality, index arbitrage, index fund, joint-stock company, locking in a profit, Long Term Capital Management, Louis Bachelier, margin call, market clearing, merger arbitrage, money market fund, Myron Scholes, Paul Samuelson, price stability, random walk, Richard Thaler, risk tolerance, Robert Bork, Robert Shiller, Robert Shiller, Ronald Reagan, shareholder value, short selling, stocks for the long run, the market place, transaction costs

(New investment trusts were created at a furious pace throughout most of 1929, with a new trust appearing approximately every business day.) The hypothetical new trust would be capitalized at perhaps $150 million, of which $50 million would be raised from the sale of common stock, and $100 million from the sale of fixed-income securities, such as bonds and preferred stock. Since the holders of the bonds and preferred stock expected only to receive a fixed return, all the gains (if any) beyond the amount necessary to pay the fixed-income investors would go to the common holders. Say the value of the stocks in which the trust had invested rose by 50%. The value of the trust’s assets (before interest, preferred-stock dividends, and expenses) would increase from the original $150 million to $225 million. Since the holders of the bonds and preferred stock had a claim on only $100 million, the common shares of the trust would now be worth $125 million, or 150% more than at the creation of the trust.

Rockefeller, stating simply, “I don’t like him.”3 The feeling was mutual; Rockefeller often said of Morgan that he could not see “why any man should have such a high and mighty feeling about himself.”4 In late March 1901, Schiff began to buy Northern Pacific. Orders to purchase shares were parceled out carefully to unrelated brokers so as to disguise the buying—to avoid alerting Hill and Morgan. Schiff bought shares of Northern Pacific preferred stock in addition to the common. The preferred, unlike the common, was a fixed income security, paying a set dividend that would not rise or fall with the company’s earnings. This distinction, however, was not important to Schiff. The Northern Pacific preferred shares carried with them the same rights to elect the board of directors as did the common shares; thus Schiff bought preferred and/or common stock whenever he could without dramatically disturbing the respective prices.

Perhaps the most important was the tax-induced creation of employee pension funds that occurred during the war years. Searching for means of providing tax-deductible employee compensation not subject to wage controls, many corporations began to offer pension plans. These innovations at first had no real impact on the stock market, in that they were usually “defined benefit”h plans funded by corporate investments in fixed-income assets, not equities. Few pension fund managers considered stocks to be prudent investments. Over time, however, this would change, and pension and retirement funds would become the single most important engine driving the bull markets of the later twentieth century. Other changes, gradual yet perceptible, were also occurring. The pounding that conservative members of the Wall Street establishment had taken during the New Deal, particularly after the Whitney scandal broke, was reflected in the evolving character of the New York Stock Exchange.


pages: 219 words: 15,438

The Essays of Warren Buffett: Lessons for Corporate America by Warren E. Buffett, Lawrence A. Cunningham

buy and hold, compound rate of return, corporate governance, Dissolution of the Soviet Union, diversified portfolio, dividend-yielding stocks, fixed income, George Santayana, index fund, intangible asset, invisible hand, large denomination, low cost airline, low cost carrier, oil shock, passive investing, price stability, Ronald Reagan, the market place, transaction costs, Yogi Berra, zero-coupon bond

But there is a small problem with this line of reasoning: Using it, one must conclude that all of a value of a convertible preferred resides in the conversion privilege and that value of a nonconvertible preferred of Salomon would be zero, no matter what its coupon or terms for redemption. The point you should keep in mind is that most of the value of our convertible preferreds is derived from their fixed-income characteristics. That means the securities cannot be worth less than the value they would possess as non-convertible preferreds and may be worth more because of their conversion options. 116 CARDOZO LAW REVIEW [Vol. 19:1 Berkshire made five private purchases of convertible preferred stocks during the 1987-91 period and the time seems right to discuss their status. In each case we had the option of sticking with these preferreds as fixed-income securities or converting them into common stock. Initially, their value to us came primarily from their fixedincome characteristics. The option we had to convert was a kicker.

We are comfortable owning stock in well-run banks, and we will convert and keep our First Empire common shares. Bob Wilmers, CEO of the company, is an outstanding banker, and we love being associated with him. Our other two preferreds have been disappointing, though the Salomon preferred has modestly outperformed the fixed-income securities for which it was a substitute. However, the amount of management time Charlie and I have devoted to this holding has been vastly greater than its economic significance to Berkshire. Certainly I never dreamed I would take a new job at age 60-Salomon interim chairman, that is-because of an earlier purchase of a fixed-income security. 118 CARDOZO LAW REVIEW [Vol. 19:1 Soon after our purchase of the Salomon preferred in 1987, I wrote that I had "no special insights regarding the direction or future profitability of investment banking." Even the most charitable commentator would conclude that I have since proved my point.

Nor will the returns be as attractive as those produced when we make our favorite form of capital deployment, the acquisition of 80% or more of a fine business with a fine management. But both opportunities are rare, particularly in a size befitting our present and anticipated resources. In summation, Charlie and I feel that our preferred stock investments should produce returns moderately above those achieved by most fixed-income portfolios and that we can play a minor but enjoyable and constructive role in the investee companies. Mistakes occur at the time of decision. We can only make our mistake-du-jour award, however, when the foolishness of a decision becomes obvious. By this measure, 1994 was a vintage year with keen competition for the gold medal. Here, I would like to tell you that the mistakes I will describe originated with Charlie.


pages: 444 words: 86,565

Investment Banking: Valuation, Leveraged Buyouts, and Mergers and Acquisitions by Joshua Rosenbaum, Joshua Pearl, Joseph R. Perella

asset allocation, asset-backed security, bank run, barriers to entry, business cycle, capital asset pricing model, collateralized debt obligation, corporate governance, credit crunch, discounted cash flows, diversification, fixed income, intangible asset, London Interbank Offered Rate, performance metric, shareholder value, sovereign wealth fund, stocks for the long run, technology bubble, time value of money, transaction costs, yield curve

The most recent 10-K and 10-Q for the period ending prior to the announcement date typically serve as the source for the necessary information to calculate the target’s LTM financial statistics and balance sheet data. In some cases, the banker may use a filing after announcement if the financial information is deemed more relevant. The 10-K and 10-Q are also relied upon to provide information on the target’s shares outstanding and options/warrants.66 Equity and Fixed Income Research Equity and fixed income research reports often provide helpful deal insight, including information on pro forma adjustments and expected synergies. Furthermore, research reports typically provide color on deal dynamics and other circumstances. Private Targets A private target (i.e., a non-public filer) is not required to publicly file documentation in an M&A transaction as long as it is not subject to SEC disclosure requirements.

Study the Target The process of learning the in-depth “story” of the target should be exhaustive as this information is essential for making decisions regarding the selection of appropriate comparable companies. Toward this end, the banker is encouraged to read and study as much company- and sector-specific material as possible. The actual selection of comparable companies should only begin once this research is completed. For targets that are public registrants,4 annual (10-K) and quarterly (10-Q) SEC filings, consensus research estimates, equity and fixed income research reports, press releases, earnings call transcripts, investor presentations,5 and corporate websites provide key business and financial information. Private companies present a greater challenge as the banker is forced to rely upon sources such as corporate websites, sector research reports, news runs, and trade journals for basic company data. Public competitors’ SEC filings, research reports, and investor presentations may also serve as helpful sources of information on private companies.

As a starting point, the banker typically consults with peers or senior colleagues to see if a relevant set of comparable acquisitions already exists internally. In the event the banker is starting from scratch, we suggest searching through M&A databases, examining the M&A history of the target and its comparable companies, and reviewing merger proxies of comparable companies for lists of selected comparable acquisitions disclosed in the fairness opinions. Equity and fixed income research reports for the target (if public), its comparable companies, and overall sector may also provide lists of comparable acquisitions, including relevant financial data (for reference purposes only).As part of this process, the banker seeks to learn as much as possible regarding the specific circumstances and deal dynamics of each transaction. This is particularly important for refining the universe and, ultimately, honing in on the “best” comparable acquisitions


pages: 332 words: 81,289

Smarter Investing by Tim Hale

Albert Einstein, asset allocation, buy and hold, buy low sell high, capital asset pricing model, collapse of Lehman Brothers, corporate governance, credit crunch, Daniel Kahneman / Amos Tversky, diversification, diversified portfolio, Donald Trump, equity premium, Eugene Fama: efficient market hypothesis, eurozone crisis, fiat currency, financial independence, financial innovation, fixed income, full employment, implied volatility, index fund, information asymmetry, Isaac Newton, John Meriwether, Long Term Capital Management, Northern Rock, passive investing, Ponzi scheme, purchasing power parity, quantitative easing, random walk, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, South Sea Bubble, technology bubble, the rule of 72, time value of money, transaction costs, Vanguard fund, women in the workforce, zero-sum game

One problem is that many investors feel that, having taken on bond exposure at the expense of equity exposure, they should try to get as much juice out of the Defensive Mix as possible. Alternatively, they own some fixed income in order to generate an income to live off and again try to squeeze as much income as they can. This has material consequences. Figure 7.6 The role of bonds depends on what kind of investor you are James Tobin and the ‘whisky and water’ approach would simply suggest that you take all the risk in the growth-oriented portfolio and simply add the risk-free water to it. As such the Defensive Mix needs to be just that – it is there to protect your wealth. Theoretically that sounds both rational and simple to do. In practice it needs a little thought. In order to try to make sense of creating our defensive asset mix, we need to take a step back and ask ourselves what the bond (fixed income) part of the portfolio is there for. This is summarised in Figure 7.6.

The rewards that you receive are the regular dividends the company pays in cash, and the hope that the strategy of the company is a strong one and this will be reflected in growing profits, and a rise in the price of its shares over time. The second is to lend your money to someone, be it an individual (not usually recommended), a corporation or a government. In return, investors receive interest (usually referred to as a coupon) and their capital back at the maturity date of the loan. Loan instruments are often called ‘fixed income’ securities, because the interest is fixed at the outset, or, alternatively they are called bonds. In general, the higher the risk of not getting your money back and the longer the time you lend your money for, the higher the rate of interest you will expect to be paid by the borrower. When you next place a bank deposit, remember that you are lending your money to the bank. Perhaps in this context, Icesave’s and Northern Rock’s high deposit rates were telling a useful story – their strategies were risky.

What we should be interested in is whether, after all the costs incurred in investing are accounted for, any inefficiencies that exist can be exploited by active managers to generate market-beating returns consistently over time. To draw a conclusion we need to look at the track record of active managers as a collective group, to see if they do. We study the evidence a little later. Signs of efficiency include a narrow dispersion of longer-term returns between the top and bottom managers, as no one has a truly sustainable advantage or disadvantage. On this basis, the fixed income markets are reasonably efficient, as are equity markets such as the USA and the UK. Active managers invariably claim that their market-beating approach will work better in less-efficient markets, such as small company stocks or small overseas equity markets, as they theoretically have the ability to exploit these inefficiencies. However, always remember that even in markets where information is deemed to be less than perfect, if the anomalies cannot be exploited to exceed the transaction costs involved with investing in them, then active management for you or me is worthless.


pages: 389 words: 81,596

Quit Like a Millionaire: No Gimmicks, Luck, or Trust Fund Required by Kristy Shen, Bryce Leung

"side hustle", Affordable Care Act / Obamacare, Airbnb, asset allocation, barriers to entry, buy low sell high, call centre, car-free, Columbine, cuban missile crisis, Deng Xiaoping, Elon Musk, fear of failure, financial independence, fixed income, follow your passion, hedonic treadmill, income inequality, index fund, longitudinal study, low cost airline, Mark Zuckerberg, mortgage debt, obamacare, offshore financial centre, passive income, Ponzi scheme, risk tolerance, risk/return, Silicon Valley, single-payer health, Snapchat, Steve Jobs, supply-chain management, the rule of 72, working poor, Y2K, Zipcar

Inflation is the bane of retirement planners everywhere. Traditional retirement planning means investing heavily in equities when a person is young, then shifting into fixed-income assets like bonds over time. Once the person hits sixty-five, the majority of their portfolio is in bonds, and the danger is a spike in inflation after retirement, in which case their fixed income won’t keep up with the cost of living. My investing strategy avoids this situation entirely. I’ve achieved income stability not by shifting into fixed income but by using a combination of the Yield Shield, the Cash Cushion, and Buckets and Backups. My portfolio never flips into a majority-fixed-income allocation. And because I’ll stay invested in equities throughout retirement, my portfolio is naturally hedged against inflation. This is because companies sell goods to people, and when people pay more money for their goods (like that cup of coffee) because of inflation, that company is making more money.

MY FIRST PORTFOLIO So, there we were in our first apartment, two years into our careers, huddled around the computer with printed-out charts and papers scattered throughout our bedroom. The research was done, our portfolio designed, our investment funds picked out, and our combined life savings ($100,000) sitting in our brokerage accounts, waiting for their marching orders. Here’s the portfolio Bryce and I decided on: It had a 60 percent equity/40 percent fixed-income asset allocation, with the equity portion split evenly among Canada, the United States, and EAFE. “Ready?” Bryce asked. “Yes. I . . . I think . . . ,” I stammered. My heart raced. This was the first truly “rich person” thing I had ever done. I had gone from being relieved to have any money at all to learning how to grow it. The girl who dug for toys in a medical waste heap was about to invest in the stock market.

It said to sell the only asset that wasn’t on fire (bonds) and buy more stocks even as the markets continued to plummet. I didn’t know it at the time, but this turned out to be the exact right thing to do. Limits to Rebalancing Before I go any further, I have to warn you about a few limitations to this approach. First, Modern Portfolio Theory only works if a portfolio has some fixed income as well as some equity. This system breaks down if you’re too tilted one way or the other. For example, during a stock market crash like the one we had, if I had been holding 100 percent equity, rebalancing wouldn’t work. As the stock market plummeted, there would have been no complementary asset that would rise, so my allocations wouldn’t have changed and I’d have had nothing to rebalance. That’s why I advise not going above 80 percent equity, even if you’re an aggressive investor.


Concentrated Investing by Allen C. Benello

activist fund / activist shareholder / activist investor, asset allocation, barriers to entry, beat the dealer, Benoit Mandelbrot, Bob Noyce, business cycle, buy and hold, carried interest, Claude Shannon: information theory, corporate governance, corporate raider, delta neutral, discounted cash flows, diversification, diversified portfolio, Edward Thorp, family office, fixed income, high net worth, index fund, John von Neumann, Louis Bachelier, margin call, merger arbitrage, Paul Samuelson, performance metric, random walk, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, shareholder value, Sharpe ratio, short selling, survivorship bias, technology bubble, transaction costs, zero-sum game

We actually got out before then. Outside its holding in Sequoia, and its brief flirtation with a technology investor, Grinnell also directly held between 8 to 10 other stocks, but little in the way of cash and fixed income. Rosenfield and Gordon purposely minimized Grinnell’s exposure to fixed income:67 We didn’t really like having fixed income. We always had the philosophy that cash was the inverse relationship of having enough good ideas. We didn’t have asset allocation, no consultant. If we had enough good ideas, we had zero cash. Grinnell College: The School of Concentration 169 The board, however, wanted Gordon to hold more in fixed income so that the endowment didn’t need to sell stocks to pay the college’s operating expenses. The board would say, “You’re encroaching upon endowment:”68 The board would say, “You’ve had to sell stocks to give us our 5 percent,” if we’d be fully invested.

If they’re trying to find 100 great investments a year, that’s impossible. Grinnell’s investment team continued the practice of employing outside investment managers, who now manage 80 percent of the capital, up from 60 percent under Gordon.84 Grinnell’s capital is allocated 45 percent to stocks, 45 percent to alternative investments, and 10 percent to cash and fixed-income instruments. The biggest change is that Grinnell focuses on the cash and fixed-income portion of the college’s investment holdings, Grinnell College: The School of Concentration 173 while outside managers handle the stock portfolio. Grinnell continues to have some private investments directly managed by the endowment. Wilson eschews “macro” money managers who bet on big-picture theses, preferring managers whose performance is repeatable.85 He favors managers who rely on analysis, rather than instinct or “gut feelings,” as Wilson describes it.86 Another significant shift is the focus on international investments.

After his stint in the Treasury, on his return to Cambridge in November 1919, he was appointed Second Bursar. The First Bursar was responsible for the financial administration of King’s College, which might encompass anything from collecting tuition fees to managing assets, and the Second Bursar acted as assistant to the First. Cambridge was subject to a statute and to the Trustee Act, which restricted its investment holdings to high‐grade fixed income securities.53 By mid‐1920, Keynes had persuaded the college to carve out from the endowment a separate portfolio not subject to the restrictions of the legislation.54 The new portfolio would contain common John Maynard Keynes: Investor Philosopher 47 stock, currency, and commodity futures.55 Though Keynes shifted some of the capital out of long‐term government bonds, the endowment maintained its income level, which was important because endowment income was not reinvested in the portfolio, but rather directed to spending.


pages: 1,042 words: 266,547

Security Analysis by Benjamin Graham, David Dodd

activist fund / activist shareholder / activist investor, asset-backed security, backtesting, barriers to entry, business cycle, buy and hold, capital asset pricing model, carried interest, collateralized debt obligation, collective bargaining, corporate governance, corporate raider, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, diversified portfolio, fear of failure, financial innovation, fixed income, full employment, index fund, intangible asset, invisible hand, Joseph Schumpeter, locking in a profit, Long Term Capital Management, low cost airline, low cost carrier, moral hazard, mortgage debt, Myron Scholes, Right to Buy, risk-adjusted returns, risk/return, secular stagnation, shareholder value, The Chicago School, the market place, the scientific method, The Wealth of Nations by Adam Smith, transaction costs, zero-coupon bond

And yet I came away with a negative reaction as well, feeling that it contained too much dogma and too many formulas incorporating numerical constants like “multiply by x” or “count only y years.” My more recent reading of the chapters on fixed income securities in the 1940 edition of Security Analysis served to remind me of some of the rules I had found too rigid. But it also showed me the vast wealth of less quantitative and more flexible common sense contained in the book, as well as some of the forward-looking insights. To my mind, some of the most interesting aspects of the book—and of developments in the investment world over the last several decades—are seen in Graham and Dodd’s perspective on the evolution of investment standards. • At least through 1940, there were well-accepted and very specific standards for what was proper and what was not, especially in fixed income. Rules and attitudes governed the actions of fiduciaries and the things they could and could not do.

The securities performed as promised, of course, but there were a couple of developments that Graham and Dodd did not and could not foresee. First and foremost were the ravaging effects of inflation in the late 1970s and early 1980s. The inflationary spiral ultimately led to higher interest rates and large losses for bond investors. Second was the expansion of the fixed income markets and the proliferation of innumerable fixed income securities that created opportunities for value investing in the bond market for those willing to sift through vast numbers of similar instruments in search of anomalous pricing. Graham and Dodd advised profit-seeking investors, both large and small, to purchase securities trading below their intrinsic value, and they suggested that investors submit their analytical work for critique by others.

The third handicap to security analysis is found in the market itself. In a sense the market and the future present the same kind of difficulties. Neither can be predicted or controlled by the analyst, yet his success is largely dependent upon them both. The major activities of the investment analyst may be thought to have little or no concern with market prices. His typical function is the selection of high-grade, fixed-income-bearing bonds, which upon investigation he judges to be secure as to interest and principal. The purchaser is supposed to pay no attention to their subsequent market fluctuations, but to be interested solely in the question whether the bonds will continue to be sound investments. In our opinion this traditional view of the investor’s attitude is inaccurate and somewhat hypocritical. Owners of securities, whatever their character, are interested in their market quotations.


pages: 250 words: 77,544

Personal Investing: The Missing Manual by Bonnie Biafore, Amy E. Buttell, Carol Fabbri

asset allocation, asset-backed security, business cycle, buy and hold, diversification, diversified portfolio, Donald Trump, employer provided health coverage, estate planning, fixed income, Home mortgage interest deduction, index fund, Kickstarter, money market fund, mortgage tax deduction, risk tolerance, risk-adjusted returns, Rubik’s Cube, Sharpe ratio, stocks for the long run, Vanguard fund, Yogi Berra, zero-coupon bond

It’s a good idea to keep some money in shortterm investments so you don’t have to sell long-term investments when their values are down. • Reinvestment risk. When you invest in bonds, bills, or even certificates of deposit and hold them until they mature, you face reinvestment risk, the risk that interest rates are lower when your fixed-income investment matures and that you have to reinvest your money in a new investment with a lower interest rate. Unfortunately, reinvestment risk is a fact of life with any kind of fixed-income investment you hold to maturity. • Interest rate risk. If you buy a bond and sell it before it matures, you face interest rate risk, the risk that the bond price drops because interest rates rise (see page 136). • Currency risk. If you invest in foreign stocks or bonds, currency risk comes into play.

For example, the Charles Schwab website has a risk profile questionnaire (http://tinyurl.com/ schwabriskprofile) that analyzes your risk tolerance and investment timeframe to determine what type of investor you are. 160 Chapter 9 But because your stocks need time to recover from the bottom of a business cycle or bad news about a company, you also need other types of investments. Enter fixed-income investments, which deliver more dependable returns. Although bond returns sometimes don’t beat inflation, you use bonds and other fixed-income investments for overall portfolio stability. In effect, you take on small risks, like interest rate risk and reinvestment risk, to counteract the risks from stocks. REITs offer both attractive dividends and potential capital appreciation, so they help reduce overall risk further. As you’ll learn on page 190, you also keep money you’ll need in the near future in very safe investments like short-term bonds, money market accounts, certificates of deposit, or savings accounts.

Can you earn attractive returns without too much risk? It turns out you can have it both ways, as you’ll learn on page 160. The table below compares returns for intermediate- and long-term fixedincome investments, large stocks, and small stocks, from 1926 through the end of 2008. As you can see, the long-term average annual returns and real returns (that is, the return adjusted for inflation) for stocks are almost twice those for fixed-income investments. For example, the real return for government bonds beats inflation by only a few percentage points. (Treasury bills [not listed below], which are short-term government bonds, delivered a real return of only 0.7% during the same period.) The single best years for stocks are likely to make you salivate. However, if you had everything riding on small-company stocks and retired just before the Depression, you would have lost almost 90% of your retirement fund between 1929 and 1932, which is why the Great Depression was so grim and why you want a diversified portfolio that delivers more consistent returns from year to year.


pages: 351 words: 102,379

Too big to fail: the inside story of how Wall Street and Washington fought to save the financial system from crisis--and themselves by Andrew Ross Sorkin

affirmative action, Andy Kessler, Asian financial crisis, Berlin Wall, break the buck, BRICs, business cycle, collapse of Lehman Brothers, collateralized debt obligation, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Emanuel Derman, Fall of the Berlin Wall, fear of failure, fixed income, Goldman Sachs: Vampire Squid, housing crisis, indoor plumbing, invisible hand, London Interbank Offered Rate, Long Term Capital Management, margin call, market bubble, Mikhail Gorbachev, money market fund, moral hazard, naked short selling, NetJets, Northern Rock, oil shock, paper trading, risk tolerance, Robert Shiller, Robert Shiller, rolodex, Ronald Reagan, savings glut, shareholder value, short selling, sovereign wealth fund, supply-chain management, too big to fail, value at risk, éminence grise

But given a chance to back out of the deal, Fuld declined. The firm had made a commitment and it was going to stick with it. Gregory made a circuit to rally the troops. “This is going to be temporary,” he told Lehman colleagues. “We’re going to fight through this.” As both Gregory and Fuld were fixed-income traders at heart, they weren’t entirely up to speed on how dramatically that world had changed since the 1980s. Both had started in commercial paper, probably the sleepiest, least risky part of the firm’s business. Fixed-income trading was nothing like Fuld and Gregory knew in their day: Banks were creating increasingly complex products many levels removed from the underlying asset. This entailed a much greater degree of risk, a reality that neither totally grasped and showed remarkably little interest in learning more about.

The firm was making bigger bets than it would ever be good for and nobody in the executive office seemed to understand or care. To criticize the firm’s direction was to be branded a traitor and tossed out the door. Among those who tried to sound the alarm was Michael Gelband, who had been Lehman’s head of fixed-income trading for two years and had known Gregory for two decades. In late 2006, in a discussion with Fuld about his bonus, Gelband remarked that the good times were about to hit a rough patch, for which the firm was not well positioned. “We’re going to have to change a lot of things,” he warned. Fuld, looking unhappy, said little in reply. The fixed-income guys had been spending a lot of time talking about the train wreck that awaited the U.S. economy. In February 2007, Larry McCarthy, Lehman’s top distressed-debt trader, had delivered a presentation to his group in which he laid out a dire scenario.

Goldman had decided to make a major push into trading bonds, commodities, and currencies, and to take on larger risks. The firm had been a pioneer in commercial paper and a leader in municipal finance, but remained an also-ran in fixed income, compared with Salomon Brothers and others. Winkelman and Jon Corzine overhauled that part of the business and recruited talent from Salomon. Impressed by Blankfein’s well-honed diplomacy and his obvious intelligence, Winkelman placed him in charge of six salesmen in currency trading and, later, the entire unit. Robert Rubin, who then ran fixed income with Stephen Friedman, was opposed to the move. “We’ve never seen it work to put salespeople in charge of trading in other areas of the firm,” Rubin told Winkelman. “Are you pretty sure of your analysis?” “Really appreciate your experience, Bob, but I think he’ll do all right,” Winkelman responded.


Financial Statement Analysis: A Practitioner's Guide by Martin S. Fridson, Fernando Alvarez

business cycle, corporate governance, credit crunch, discounted cash flows, diversification, Donald Trump, double entry bookkeeping, Elon Musk, fixed income, information trail, intangible asset, interest rate derivative, interest rate swap, negative equity, new economy, offshore financial centre, postindustrial economy, profit maximization, profit motive, Richard Thaler, shareholder value, speech recognition, statistical model, time value of money, transaction costs, Y2K, zero-coupon bond

The saving grace is that the company is not in a growth mode that requires heavy new investment in its business, Capital expenditures absorb an average of just $53 million a year during the projection period, versus EBITDA averaging $664 million. As a result, the analyst forecasts that Dex One will pay down $2.7 billion of debt as its revenues shrink, resulting in a reduction of net leverage (defined as debt minus cash divided by EBITDA) from 2.58X to 1.41X. From the standpoint of the fixed-income investors, the picture does not look as bleak as it does to equity investors accustomed to seeing forecasts that show large, steady gains in earnings. Fixed-income investors are in fact the target of the analyst's research, with particular focus on the term loans of Dex One's subsidiaries, RHD, Dex East, and Dex West. Exhibit 12.22 Dex One Corporation: Best-Case Projection CONCLUSION Of the various types of analysis of financial statements, projecting future results and ratios requires the greatest skill and produces the most valuable findings.

For the last nine years of that span, participants in the Institutional Investor All-America research survey ranked Fridson number one in high yield bond strategy. Fridson has served as president of the Fixed Income Analysts Society, governor of the Association for Investment Management and Research (now CFA Institute), and director of the New York Society of Security Analysts. Since 1989 he has been book review editor of the Financial Analysts Journal. The New York Times described Fridson as “one of Wall Street's most thoughtful and perceptive analysts.” Investment Dealers Digest called him “perhaps the most well-known figure in the high yield world.” In 2000, Fridson became the youngest person inducted into the Fixed Income Analysts Hall of Fame. The Financial Management Association named him Financial Executive of the Year in 2002. Fridson is the author of six books on investments and political economy.

Still, the company disclosures provide useful information on tax effects and such accounting matters as expected changes in asset valuations and the effects of conforming the two companies’ treatment of discretionary items. MULTIYEAR PROJECTIONS So far, this chapter has focused on one-year projections and pro forma adjustments to current financial statements. Such exercises, however, represent nothing more than the foundation of a complete projection. A fixed-income investor buying a 30-year bond is certainly interested in the issuer's financial prospects beyond a 12-month horizon. Similarly, a substantial percentage of the present value of future dividends represented by a stock's price lies in years beyond the coming one. Even if particular investors plan to hold the securities for one year or less, they have an interest in estimating longer-term projections.


pages: 77 words: 18,414

How to Kick Ass on Wall Street by Andy Kessler

Andy Kessler, Bernie Madoff, buttonwood tree, call centre, collateralized debt obligation, family office, fixed income, hiring and firing, invention of the wheel, invisible hand, London Whale, margin call, NetJets, Nick Leeson, pets.com, risk tolerance, Silicon Valley, sovereign wealth fund, time value of money, too big to fail, value at risk

Again, trading government bonds and munis and corporate debt is mostly facilitating trades for clients. But there is no exchange. These are negotiated transactions. It’s you against the client, even though you are providing a service for the client. Your job is to get the best price for your firm. Some view this as screwing the client. Very confusing for outsiders. Here is a quote from Bloomberg News: Unlike equities, fixed-income trades typically are privately negotiated outside exchanges, increasing the fees traders collect by making bids and offers because they’re more difficult to execute. To make markets in debt securities, banks typically risk their own capital to buy assets from clients before lining up someone else to sell them to, sometimes making bets on the direction of markets. The new [Volker] rules are curbing that, turning traders more into middlemen.

You’ve been there long enough. Now is the time to step up – to be a hero. Every day there is some tough deal to get done. A block of shares to cross, a cleanup print to complete, a hot corporate client to reel in, a mispriced corporate bond to buy, a gamey stock deal to get done. The thing about finance is that it’s all numbers. Everything has a price. Companies that are hot have high prices. Fixed income paper that is safe have low yields. Pieces of shit have low prices. You have to think of everything in terms of its price. When a deal comes out that no one likes, it usually because the price is too high. The best way to turn a piece of shit into a Picasso is to lower the price. Don’t ever forget that. A salesman I spent a lot of time with worked out of the Chicago office. He was a junior guy so they gave him all the clients in Milwaukee and the rest of Wisconsin.

Well…generate revenue! Ah, if only it were that easy. Almost everyone on Wall Street gets paid a modest draw, modest by Wall Street means anyway, maybe $100K, maybe $150K, sometimes more, sometimes less. The rest of compensation is paid as a bonus out of that ginormous bonus pool. Usually, after the Big Kahunas at the top take their huge cut, smaller bonus pools are allocated by division, capital markets, fixed income, investment banking etc. And even then, after the co-heads of these divisions take two bonuses when probably one would do, it is allocated further to distinct trading desks and groups. That is the pool you are fighting for. Everything you have ever done to generate revenue, bring in new clients, being a hero on this deal or that will come into play. But no one is going out of their way to pay you, you have to make your case.


pages: 741 words: 179,454

Extreme Money: Masters of the Universe and the Cult of Risk by Satyajit Das

affirmative action, Albert Einstein, algorithmic trading, Andy Kessler, Asian financial crisis, asset allocation, asset-backed security, bank run, banking crisis, banks create money, Basel III, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Big bang: deregulation of the City of London, Black Swan, Bonfire of the Vanities, bonus culture, Bretton Woods, BRICs, British Empire, business cycle, capital asset pricing model, Carmen Reinhart, carried interest, Celtic Tiger, clean water, cognitive dissonance, collapse of Lehman Brothers, collateralized debt obligation, corporate governance, corporate raider, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Daniel Kahneman / Amos Tversky, debt deflation, Deng Xiaoping, deskilling, discrete time, diversification, diversified portfolio, Doomsday Clock, Edward Thorp, Emanuel Derman, en.wikipedia.org, Eugene Fama: efficient market hypothesis, eurozone crisis, Everybody Ought to Be Rich, Fall of the Berlin Wall, financial independence, financial innovation, financial thriller, fixed income, full employment, global reserve currency, Goldman Sachs: Vampire Squid, Gordon Gekko, greed is good, happiness index / gross national happiness, haute cuisine, high net worth, Hyman Minsky, index fund, information asymmetry, interest rate swap, invention of the wheel, invisible hand, Isaac Newton, job automation, Johann Wolfgang von Goethe, John Meriwether, joint-stock company, Jones Act, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, Kevin Kelly, laissez-faire capitalism, load shedding, locking in a profit, Long Term Capital Management, Louis Bachelier, margin call, market bubble, market fundamentalism, Marshall McLuhan, Martin Wolf, mega-rich, merger arbitrage, Mikhail Gorbachev, Milgram experiment, money market fund, Mont Pelerin Society, moral hazard, mortgage debt, mortgage tax deduction, mutually assured destruction, Myron Scholes, Naomi Klein, negative equity, NetJets, Network effects, new economy, Nick Leeson, Nixon shock, Northern Rock, nuclear winter, oil shock, Own Your Own Home, Paul Samuelson, pets.com, Philip Mirowski, plutocrats, Plutocrats, Ponzi scheme, price anchoring, price stability, profit maximization, quantitative easing, quantitative trading / quantitative finance, Ralph Nader, RAND corporation, random walk, Ray Kurzweil, regulatory arbitrage, rent control, rent-seeking, reserve currency, Richard Feynman, Richard Thaler, Right to Buy, risk-adjusted returns, risk/return, road to serfdom, Robert Shiller, Robert Shiller, Rod Stewart played at Stephen Schwarzman birthday party, rolodex, Ronald Reagan, Ronald Reagan: Tear down this wall, Satyajit Das, savings glut, shareholder value, Sharpe ratio, short selling, Silicon Valley, six sigma, Slavoj Žižek, South Sea Bubble, special economic zone, statistical model, Stephen Hawking, Steve Jobs, survivorship bias, The Chicago School, The Great Moderation, the market place, the medium is the message, The Myth of the Rational Market, The Nature of the Firm, the new new thing, The Predators' Ball, The Wealth of Nations by Adam Smith, Thorstein Veblen, too big to fail, trickle-down economics, Turing test, Upton Sinclair, value at risk, Yogi Berra, zero-coupon bond, zero-sum game

Like the original, the logo’s background is blood red, and the skull and bones are black. The next day, JR will be crowned Hedge Fund of the Year and Hedge Fund Manager of the Year at the all-star gala Global Finance Forum. Mailer’s bank is also getting an award—Fixed Income House of the Year. Mailer bought that prize of course. The idea behind industry awards is that clients and peers vote on who is the best. A dealer voted best “something in something somewhere” uses it prominently to solicit clients. Polling is supposedly anonymous and independent. Like democracy, the process is obscure. Mailer “heard” that his bank would be crowned Fixed Income House of the Year. If this were correct, he explained to the magazine arranging the awards, then he would buy a platinum sponsorship of the award event (cost $100,000) and take a full-page ad (cost $40,000).

Mailer’s turn. “Years. Many years.” It is autumn 2007. I am in London to brief Mailer’s bank on conditions in credit markets. Mailer ruminates on my gloomy prognostications, drains his drink, and tries to order another. The bartender has trouble understanding Mailer’s Bostonian rolled vowels and laryngeal consonants. When I first met Mailer, he introduced himself as: “Mailer Stevenson. Managing director. Fixed income. Graduate School of Business, Chicago.” Mailer then worked at a white-shoe Wall Street firm. Used to describe pedigreed investment banks, “white shoe” is a reference to “white bucks,” a laced suede or buckskin shoe once popular among upper-class, Ivy League-trained bankers. Losing out in the internecine wars that break out periodically in investment banks, Mailer moved to London to lead the trading operations of Euro Swiss Bank (ESB), a major European bank.

Ken Livingstone, later London’s mayor, argued that an aquarium built for the same cost would attract more tourism. Author Rita Hatton pointed out that The Physical Impossibility of Death in the Mind of Someone Living was both an aquarium and a tourist attraction.3 JR was rumored to have commissioned Hirst to create an installation for its new offices, using white pointer sharks, a feared large predator. Retreat The bad blood between Mailer and JR dates to Mailer’s time as the head of fixed income at ESB. Each year, the bank held its Global Strategy Session (GSS) at Versailles. Sceptics referred to it secretly as the God Sun King Speaketh. Eduard Keller, the young, urbane, and snappily dressed chief executive of ESB, was the Sun King. Keller, a former management consultant, knew little about banking. He spoke of competitive gaps (ESB lagged other banks) that Mailer had been hired to bridge.


pages: 348 words: 82,499

DIY Investor: How to Take Control of Your Investments & Plan for a Financially Secure Future by Andy Bell

asset allocation, bank run, buy and hold, collapse of Lehman Brothers, credit crunch, diversification, diversified portfolio, estate planning, eurozone crisis, fixed income, high net worth, hiring and firing, Isaac Newton, Kickstarter, lateral thinking, money market fund, Northern Rock, passive investing, place-making, quantitative easing, selection bias, short selling, South Sea Bubble, technology bubble, transaction costs, Vanguard fund

Mixed asset funds have set percentages that can be invested in different asset classes, typically equities and fixed income investments such as corporate and government bonds, and cash. UK All Companies funds, for example, are defined by the IMA as ‘funds which invest at least 80 per cent of their assets in UK equities which have a primary objective of achieving capital growth’. However, funds within any IMA sector may have widely varying asset mixes, strategies and risk profiles. Income – fixed income/equity/mixed asset Income funds invest in fixed-income assets such as corporate and government bonds, in dividend-generating equities or a combination of the two. Fixed-income sectors include UK Gilts, Sterling Corporate Bonds and Sterling Strategic Bond funds. Funds in the Sterling High Yield sector are riskier, with at least 80 per cent of their assets required to be in UK corporate bonds rated below, or more risky than, BBB–.

These two statements oversimplify what is a complex interaction between market expectations of interest rates and the price of a bond, which is also influenced by inflation, wider views of the economy and many other factors. People often mistakenly believe that because bond investments are promoted as being safer than equity investments, that they carry some form of capital protection. They don’t, unless you hold them to maturity. Inflation-linked bonds High inflation erodes the value of fixed-income bonds, which is what most conventional gilt and corporate bonds are. If you are concerned about inflation you can opt for bonds that increase their payout in line with inflation. National Grid issued the first inflation-linked corporate bond ever to be made available to retail investors in 2011, paying 1.25 per cent above the Retail Price Index. Since then Tesco has launched one paying 1 per cent above RPI.

If you hold bonds personally through a Dealing Account, you will account for any tax due via your self-assessment tax return. There is no stamp duty when you buy bonds. Permanent interest-bearing shares (PIBS) Permanent interest-bearing shares (PIBS) are a special class of share issued by building societies. They pay a fixed rate of interest and can be bought and sold on the stock exchange. They have some of the characteristics of a corporate bond, in that they pay a fixed income on a regularly basis, but they normally run for an indeterminate period. Some PIBS, however, have a ‘call date’, which gives the issuer the right to buy the PIBS back from you if it wants to. Unlike the fixed-term interest deals that building societies are well known for, PIBS do not benefit from the protection of the Financial Services Compensation Scheme. PIBS that were issued by building societies that have subsequently demutualised are called perpetual sub-bonds (PSBs).


Hedgehogging by Barton Biggs

activist fund / activist shareholder / activist investor, asset allocation, backtesting, barriers to entry, Bretton Woods, British Empire, business cycle, buy and hold, diversification, diversified portfolio, Elliott wave, family office, financial independence, fixed income, full employment, hiring and firing, index fund, Isaac Newton, job satisfaction, margin call, market bubble, Mikhail Gorbachev, new economy, oil shale / tar sands, paradox of thrift, Paul Samuelson, Ponzi scheme, random walk, Ronald Reagan, secular stagnation, Sharpe ratio, short selling, Silicon Valley, transaction costs, upwardly mobile, value at risk, Vanguard fund, zero-sum game, éminence grise

Everybody was deeply embarrassed, and ever since the big institutions have been obsessed with risk analytics and throw around terms like stress-testing portfolios, value at risk (VAR), and Sharpe ratios. The funds of funds employ sophisticated quantitative analytics to add value by strategically allocating among the different hedge-fund classes.The hedge-fund universe is usually broken down into seven broad investment style classifications.These are event driven, fixed-income arbitrage, global convertible bond arbitrage, equity market-neutral, long/short equity, global macro, and commodity trading funds. Each has its own, unique performance cycle. One year a fund of funds will be heavy in macro and long/short equity funds and be out of or have very little in equity market neutral and convertible arbitrage. The next year the allocation will be completely different.

In fact, a study issued in mid-2005 of 4,000 private equity funds by Private Equity Intelligence found that the top 25% of funds by size raised each year between 1998 and 2003 beat the industry’s performance by six percentage points in Europe and two percentage points in the United States. Two-thirds of the 24 European jumbo funds in the sample beat the average. Swensen maintains that in private equity the poor and mediocre performers stay that way. Just being in the asset class won’t do it. It’s very important to be with the real pros. He emphasizes that the difference between the twenty-fifth and seventy-fifth percentiles among U.S. fixed income managers is minimal, and even among equity managers it’s only three percentage points a year. But in the universe of private equity funds, this same performance differential exceeds 20 percentage points per annum. The Yale Endowment’s numbers are proof of this view. Its large private equity portfolio earned 37.6% over the 10 years that ended June 30, 2004, outperforming the return of a pool of private equity managers, compiled by the consulting firm Cambridge Associates, by 14.7% a year.

Meanwhile, today, back in the good old United States of America you might think private equity firms would be suffering because the IPO market has been slow and selective.They need to book gains to get paid their fees. However, the private equity guys are ingenious, and they have found a new escape hatch. The investment world is desperate for yield because interest rates on Treasury bonds are so meager. As a result, fixed income investors are reaching for yield by buying heavily into high yield, or in the parlance, junk bonds.The spread between the yield on junk and Treasuries is close to an all-time low. Everyone seems to have forgotten that from time to time, just when the buyers are frothing at the mouth about a new era, junk lives up to its name and defaults soar. Reaching for yield over time has proved to be extremely hazardous to your financial health.


pages: 444 words: 151,136

Endless Money: The Moral Hazards of Socialism by William Baker, Addison Wiggin

Andy Kessler, asset allocation, backtesting, bank run, banking crisis, Berlin Wall, Bernie Madoff, Black Swan, Branko Milanovic, break the buck, Bretton Woods, BRICs, business climate, business cycle, capital asset pricing model, commoditize, corporate governance, correlation does not imply causation, credit crunch, Credit Default Swap, crony capitalism, cuban missile crisis, currency manipulation / currency intervention, debt deflation, Elliott wave, en.wikipedia.org, Fall of the Berlin Wall, feminist movement, fiat currency, fixed income, floating exchange rates, Fractional reserve banking, full employment, German hyperinflation, housing crisis, income inequality, index fund, inflation targeting, Joseph Schumpeter, Kickstarter, laissez-faire capitalism, land reform, liquidity trap, Long Term Capital Management, McMansion, mega-rich, money market fund, moral hazard, mortgage tax deduction, naked short selling, negative equity, offshore financial centre, Ponzi scheme, price stability, pushing on a string, quantitative easing, RAND corporation, rent control, reserve currency, riskless arbitrage, Ronald Reagan, school vouchers, seigniorage, short selling, Silicon Valley, six sigma, statistical arbitrage, statistical model, Steve Jobs, stocks for the long run, The Great Moderation, the scientific method, time value of money, too big to fail, upwardly mobile, War on Poverty, Yogi Berra, young professional

It should also be no surprise that he was first to volunteer PIMCO’s fixed income management services for the new TARP facility, and is one of a chosen few to fund the Public-Private Investment Program (PIPP) unveiled in March 2009. Fellow Democrat Paulson, who placed a caveat that his decisions on running the TARP fund “may not be reviewed by any court of law or any administrative agency” would then be free to choose the fund’s manger. PIMCO offered its services for free, but fund companies have a habit of waiving fees initially and then raising them later. Paulson had carte blanche to accommodate PIMCO. Managing TARP side-by-side with private assets is a horrendously conflicted position, perhaps another factor why Gross would want to be an insider to what may soon be the world’s largest fixed-income market maker. In his September 2008 Investment Outlook, Gross opened with three paragraphs full of gushing praise for Cramer.

In essence this rescinded the citizenry’s constitutional right to private property. Through the founding of the Fed, also in 1913, the United States government regained the ability to print money extensively, which led to inflation that undercut the value of the dollar by nearly 50 percent over the ensuing three years. This eroded the purchasing power of those who bought some $17 billion of Liberty Bonds or otherwise lived on fixed income streams. (For comparison, nominal GDP had been about $32 billion in the 1907-1911 period.) While gold could still be demanded in exchange for dollars, an inconvenient check on government, during the interwar years creditors and debtors would become more apt to expand their balance sheets by pyramiding paper atop gold reserves. The scale of this fiscal and monetary intervention would sow the seeds of the destruction of what was left of the diluted gold standard by the advent of the Great Depression, a period discussed later in this chapter.

But if we insert a penny anyway, we nonetheless cheer when the lights go back on, because we can go back to what we were doing before we were unexpectedly interrupted. When in October the stock market followed the credit market into the abyss, the lights flickered off. Despite unparalleled intervention, well into 2009 there remains a huge standoff between borrowers and lenders, and an inability for most market participants to comprehend why market prices for fixed income securities could sink below rationally computed values. The U.S. economy is creaking under the weight of public and private debt that reached 364 percent of GDP in 2008, up from 267 percent 10 years earlier and 188 percent 25 years previously. This is well above levels for the last century, including the Depression-era when the denominator, economic output, collapsed. Should there be a reversion to the mean underway, it would imply deflation, reduced economic activity, and an even higher ratio of debt to GDP, just as was the case in the Great Depression.


pages: 261 words: 70,584

Retirementology: Rethinking the American Dream in a New Economy by Gregory Brandon Salsbury

Albert Einstein, asset allocation, buy and hold, carried interest, Cass Sunstein, credit crunch, Daniel Kahneman / Amos Tversky, diversification, estate planning, financial independence, fixed income, full employment, hindsight bias, housing crisis, loss aversion, market bubble, market clearing, mass affluent, Maui Hawaii, mental accounting, mortgage debt, mortgage tax deduction, negative equity, new economy, RFID, Richard Thaler, risk tolerance, Robert Shiller, Robert Shiller, side project, Silicon Valley, Steve Jobs, the rule of 72, Yogi Berra

The absence of one of these points of reference makes it impractical to plan financially to meet your objective or to assign an appropriate level of risk to your investment decisions. Traditionally, long-term investors have opted for greater risk on the belief that it would, over the right period of time, produce greater rewards. For example, historical data suggested that equity investments tend to outperform fixed income investments over time. However, the day-to-day volatility of the stock market generally makes equity investments a risky bet for short-term needs. In the context of retirement planning, equity investments provide long-term growth potential and a hedge against inflation but have greater volatility. Therefore, having equities as part of your retirement portfolio may be the right move. On the other hand, if you have immediate income needs or plan to draw income from your portfolio in the near future, investments that guarantee the return of your principal may be smarter, even though the actual rates of return on these investments may be less attractive.

A story I read recently detailed that some retirees have stopped questioning their physicians and pharmacists about side effects and dosing for their medicine; now their questioning is entirely about cost! In fact, some people who are too well-off for government health insurance, but can’t afford their own insurance, are often weighing the needs of taking maintenance medications against more immediate needs, like food and shelter.32 When you retire, you will likely be on a fixed income. It may be a large income or it may be a small one, but you can rest assured that your health will require more attention and more money during your retirement. Indeed, your health will take a bigger percentage of your budget every day, every month, every year. People in and approaching retirement in most of the past decade have “debt loads that their parents would not have considered,” according to Sally Hurme of the AARP.33 Don’t be overconfident about your health or the certainty of government programs to be there for you.

Since 1982, America has embarked on a tremendous economic expansion that would take us through the dot.com bust at the millennium. During that period there was only one recession of note. But one thing that people forget about during that era of general prosperity is that inflation still existed. It may have been 1% or 2% annually, but it was still there. Even at that low level, inflation was doing what it always does: taking away purchasing power from consumers, especially consumers on a fixed income, such as retirees. Because the rate of inflation was relatively low, however, people didn’t pay much attention to it. Instead, they looked at their nominal returns over those years. A person who invested in the stock market on January 29, 1982, when the DJIA was 871.10, didn’t necessarily have 12.5 times more buying power with that money on January 31, 2000, when the Dow was 10,940.53.7 Many dollars that were invested in the stock market in 1982 and stayed there for the following 18 years increased many times in value, at a rate that far outpaced inflation.


pages: 459 words: 118,959

Confidence Game: How a Hedge Fund Manager Called Wall Street's Bluff by Christine S. Richard

activist fund / activist shareholder / activist investor, Asian financial crisis, asset-backed security, banking crisis, Bernie Madoff, Blythe Masters, buy and hold, cognitive dissonance, collateralized debt obligation, corporate governance, corporate raider, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, Donald Trump, family office, financial innovation, fixed income, forensic accounting, glass ceiling, Long Term Capital Management, market bubble, money market fund, moral hazard, old-boy network, Ponzi scheme, profit motive, short selling, statistical model, white flight, zero-sum game

By late 2007, confidence in one financial institution after another cratered on fears they weren’t admitting the full extent of their losses, including those on massive portfolios of super-senior CDOs. “Anything else before we end for the day?” the other attorney asked. Ackman seized his chance. “It is worth remembering,” Ackman said, “that every Wall Street firm does a huge amount of business with the bond insurers, including MBIA, Ambac, and FSA. Frankly, the fixed-income markets are what have saved investment-banking profits, because the IPO [initial public offering] market is basically gone. That means MBIA might just be the biggest business generator on Wall Street,” Ackman added. “No one wants me to be right on MBIA.” The SEC attorneys told Ackman they’d be happy to hear his concerns about MBIA if he wanted to come back at a later date. Of course, he wanted to come back, Ackman told his attorney, Stein.

He described how the incentives to securitize and sell mortgages created enormous moral hazard in the mortgage market, how faulty structures allowed billions of dollars of doomed securities to be built out of the riskiest parts of bonds, and how small losses on $100 billion portfolios of collateralized-debt obligations (CDOs) could wipe out a bond insurer’s entire capital base. He also reviewed other issues specific to the insurance department’s role in overseeing the bond insurers, such as how bond insurers were engaging in prohibited credit-default swaps (CDSs) and how MBIA’s growing fixed-income arbitrage business amounted to a disguised dividend from its regulated insurance subsidiary. Ackman argued that Dinallo couldn’t stand by and allow the credit-rating companies to usurp the department’s role as the de facto regulator of bond insurers. The ABX index referencing triple-B-rated subprime mortgage bonds indicated investors expected to recover just 65 cents on the dollar for those bonds before the credit-rating companies began to downgrade the debt, he said.

There was strong demand for bond insurance, and the premiums that insurers could command in the current market had improved, said Patrick Kelly, head of CDOs and structured products at MBIA. “We want to take advantage of the current situation where we can, even in the ABS CDO market,” Kelly said. “We also want to avoid getting stuffed with the risk that people are just looking to get off their own books.” THREE WEEKS LATER, on August 24, 2007, Merrill Lynch’s head of fixed income, Osman Semerci, along with three other executives from Merrill, boarded a helicopter for the short flight to MBIA’s Armonk headquarters. Janet Tavakoli, a CDO guru who runs her own structured finance research firm in Chicago, later dubbed Merrill Lynch’s last-ditch effort to dump toxic securities on MBIA the “Apocalypse Now helicopter ride,” a reference to the scene in the Francis Ford Coppola movie in which U.S. helicopters level a Vietcong village while blaring Wagner’s highly dramatic “Ride of the Valkyries.”


pages: 422 words: 113,830

Bad Money: Reckless Finance, Failed Politics, and the Global Crisis of American Capitalism by Kevin Phillips

algorithmic trading, asset-backed security, bank run, banking crisis, Bernie Madoff, Black Swan, Bretton Woods, BRICs, British Empire, business cycle, buy and hold, collateralized debt obligation, computer age, corporate raider, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, currency peg, diversification, Doha Development Round, energy security, financial deregulation, financial innovation, fixed income, Francis Fukuyama: the end of history, George Gilder, housing crisis, Hyman Minsky, imperial preference, income inequality, index arbitrage, index fund, interest rate derivative, interest rate swap, Joseph Schumpeter, Kenneth Rogoff, large denomination, Long Term Capital Management, market bubble, Martin Wolf, Menlo Park, mobile money, money market fund, Monroe Doctrine, moral hazard, mortgage debt, Myron Scholes, new economy, oil shale / tar sands, oil shock, old-boy network, peak oil, plutocrats, Plutocrats, Ponzi scheme, profit maximization, Renaissance Technologies, reserve currency, risk tolerance, risk/return, Robert Shiller, Robert Shiller, Ronald Reagan, Satyajit Das, shareholder value, short selling, sovereign wealth fund, The Chicago School, Thomas Malthus, too big to fail, trade route

By 2008, as the financial pages trembled with the global downgrades and default problems undercutting American-made and American-exported CDOs, CDSs, CMOs, ABSs, MBSs, and ABCP, the numbers began to look a good deal more cautioning. Yes, the profits had indeed been huge. JPMorgan Chase estimated that in 2006, banks globally brought in $30 billion from their asset-backed securities business, and Bloomberg News later surmised that securitized products produced one-fifth of bank revenues during the preceding decade. In 2008, the fixed-income research firm CreditSights Inc. estimated that over-the-counter sales of derivatives accounted for as much as 40 percent of the profits of firms like Goldman Sachs and Morgan Stanley.13 However, the potential vulnerabilities were mind boggling. Back in 1993, the notional or nominal value of U.S. derivative instruments had been some $14 trillion. By 2001, it was approaching $100 trillion. Then over seven years, one of the most extraordinary and perilous transformations in world financial history would lift the 2008 total to $600 trillion.

Banks, in particular, could use these initially cheap pseudo-insurance policies as wraparounds to upgrade their speculative investments to triple-A, respecting which the bank in question would not have to hold collateral. This allowed banks to leverage themselves to the hilt and shrug off low assets quality—“we’re insured, aren’t we?” High returns drove the marketing. “It was a quest for yield,” said Don Kowalchik, fixed-income strategist at St. Louis-based A.G. Edwards. “As soon as you get all of these synthetic products based on other products, it’s a cancer that refuses to stop spreading.”15 Nonspecialist readers who have gotten this far may be starting to chuckle. Between 2001 and 2008, according to Bloomberg News, credit default swaps surged from a notional value of $681 billion to a notional value of $62 trillion.

Like digital buccaneers, and hardly more restrained than their seventeenth-century predecessors, they arbitraged the nooks and crannies of global finance, capturing even more return on capital than casino operators made from one-armed bandits and favorable gaming-table odds. As the mortgage markets seized up in mid-2007, shrewd players understood the virginity of the terrain. Jack Malvey, the chief global fixed-income strategist for Lehman Brothers, explained: “This is what we would characterize as the first correction of the neo-credit market. We’ve never had a correction with these types of institutions and these types of instruments.”3 Others distilled the doubts about hedge funds themselves—the exotic quantitative mathematics, the obscure language of fixed-leg features and two-step binomial trees, and the humongous bank loans needed for the fifteen- or twenty-to-one leverage that alchemized mere decimal points into financial Olympic gold medals.


pages: 236 words: 77,735

Rigged Money: Beating Wall Street at Its Own Game by Lee Munson

affirmative action, asset allocation, backtesting, barriers to entry, Bernie Madoff, Bretton Woods, business cycle, buy and hold, buy low sell high, California gold rush, call centre, Credit Default Swap, diversification, diversified portfolio, estate planning, fiat currency, financial innovation, fixed income, Flash crash, follow your passion, German hyperinflation, High speed trading, housing crisis, index fund, joint-stock company, money market fund, moral hazard, Myron Scholes, passive investing, Ponzi scheme, price discovery process, random walk, risk tolerance, risk-adjusted returns, risk/return, stocks for the long run, stocks for the long term, too big to fail, trade route, Vanguard fund, walking around money

This doesn’t mean I don’t ask a lot of questions, despite my confidence that at 88 you know what you are looking for in a financial professional. My job was to figure out what the money was supposed to do for him and what type of risk he was interested in taking—or budgeting, as I call it. He quickly said, “I am an income investor.” To me, that means a person that needs a high rate of income to live off of his portfolio. At this point the average stockbroker would have enough information to start putting together a list of fixed-income securities that are appropriate for a gentleman of that age. Once the box is checked, any movement is frowned upon. Why? Look at it this way, if you change a client’s profile as a broker, you may have done it wrong in the first place or are simply changing it to fit the product being sold that day. You say income, you will get income. Then I clarified his needs. He said he didn’t plan on taking any money out.

To add injury to insult, some parts of the market, even well-known areas like junk bonds, can fail to translate into a successful ETF. SPDR Barclays Capital High Yield Bond ETF (JNK) may be the worst bond strategy of all time. Now that I have your attention, let’s break down the major issues with junk bonds, and more specifically ETFs that trade baskets of those bonds. Don’t worry, there is a place for these ugly ducklings, but they are not for those trying to get fixed income risk and return. If that doesn’t keep you reading, nothing will. The junk bond market developed by Michael Milken in the 1980s is predominately a U.S. phenomenon, though they exist anywhere there is tradable debt. Simply stated, they are bonds with a poor rating. Most notably, junk bonds have higher credit risk and illiquidity, but also higher interest payments—as long as they keep paying. I want to cover the problem with junk bonds within a portfolio, the true cost of owning them, and how investors should approach the junk bond market.

After a 30-year run it could go on, but don’t you think that is a bit long in the tooth? I thought inflation and bond declines would have happened by now, but with trillions of extra dollars in the system, the bull run received a shot in the arm. One of the primary reasons for including bonds in a portfolio is the diversification factor, coupled with income generation. That said, how is an investor supposed to commit large allocations of capital in fixed income ETFs with that sinking feeling that this 30-year party may be over? MLPs are neither stock nor bond, but they can be an alternative to a portfolio seeking diversification and income outside of traditional asset classes. If you were thinking of buying higher-volatility bond ETFs like HYG, JNK, or PFD, read on and find another way to capture higher risk return and diversification. In their simplest form, MLPs are publicly traded organizations that are structured as limited partnerships (LP) rather than corporations.


pages: 304 words: 99,836

Why I Left Goldman Sachs: A Wall Street Story by Greg Smith

always be closing, asset allocation, Black Swan, bonus culture, break the buck, collateralized debt obligation, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, delayed gratification, East Village, fixed income, Flash crash, glass ceiling, Goldman Sachs: Vampire Squid, high net worth, information asymmetry, London Interbank Offered Rate, mega-rich, money market fund, new economy, Nick Leeson, quantitative hedge fund, Renaissance Technologies, short selling, Silicon Valley, Skype, sovereign wealth fund, Stanford marshmallow experiment, statistical model, technology bubble, too big to fail

The name tags, laminated cards with a bright orange border, worn on a bright orange lanyard, showed our names and universities in big black letters. We were told in no uncertain terms that we were to wear the name tags around our necks every moment we were on the premises; failure to do so would lead to big trouble. The firm wanted there to be no doubt on the trading floor as to who the interns were. Goldman ran a summer intern program in each of its divisions: one in Equities; one in Fixed Income, Currency and Commodities (FICC); one in Investment Management; one in Research, and so on. Back when I’d passed the interview process, I’d been offered two internships: one in Equities, in New York; and one in Investment Management, in Chicago. I had learned something about private wealth management the previous summer, at Paine Webber: it’s a slower business, a smaller environment. You’re dealing with individuals.

They can be complex, and they have a long and controversial history of creating havoc. But if understood correctly, derivatives can help investors hedge against (or speculate on) very specific risks. The term derivatives can be used as a catchall to include products such as options, swaps, and futures. And you can get derivatives on all asset classes: equities, foreign exchange, commodities, fixed income. At Goldman Sachs, derivatives teams were divided by asset class. Corey’s Futures Execution desk was a subsector of the broader Derivatives Sales team. I took a deep breath and told Corey the whole truth. “I did a little bit of it in college,” I said. At Stanford I’d taken a course called Economics 140, which dealt with the basics of options, futures, and other derivatives. After my summer internship, I’d taken another course on the subject, in the business school.

Some people made a mess of jamming the triplicate forms into the very thin slot of the time stamp; now and then, when things slowed down a little, Corey and I would try to top each other at the Zen of time-stamping, the goal being to insert a ticket then pull it out—zip!—in one swift and seamless motion. Someone always has to rain on your parade, though. Lloyd Blankfein, who in early 2003 was a vice chairman who oversaw the FICC (Fixed Income, Currency and Commodities) and Equities divisions, used to like to cruise by Derivatives Sales to say hello to Daffey and hear the latest buzz about his pals Jones, Bacon, and Druckenmiller. Lloyd wanted to know, “What’s the smart money doing?” One day he stopped at my desk and raised an eyebrow. “What is it with these tickets you guys are using?” he asked. “In the FICC world we don’t use tickets anymore.”


Mathematical Finance: Core Theory, Problems and Statistical Algorithms by Nikolai Dokuchaev

Black-Scholes formula, Brownian motion, buy and hold, buy low sell high, discrete time, fixed income, implied volatility, incomplete markets, martingale, random walk, short selling, stochastic process, stochastic volatility, transaction costs, volatility smile, Wiener process, zero-coupon bond

All other options can be replicated via portfolio strategies that include the stock, the option, and the bond. A similar approach can be used for the case of random r. Remember that, in our generic setting, we called the risk-free investment a bond, and it was considered as a riskfree investment. In reality, there are many different bonds (or fixed income securities). In fact, they are risky assets, similarly to stocks (discussed in the next section). If r is random, then the market can be made complete by including additional fixed income securities. © 2007 Nikolai Dokuchaev Continuous Time Market Models 101 5.12 A generalization: multistock markets Similarly, we can consider a multistock market model, when there are N stocks. Let {Si(t)} be the vector of the stock prices. The most common continuous time model for the prices is again based on Ito equations, which now can be written as Here w(t)=(w1(t),…, wn(t)) is a vector Wiener process; i.e., its components are scalar Wiener processes.

The new market can be considered as a multistock market model with N stocks (N−1 options plus the original stock). Is this market arbitrage-free? (Hint: consider first N=2 and Ti≥T.) 5.13 Bond markets Bonds are being sold an initial time for a certain price, and the owners are entitled to obtain certain amounts of cash (higher than this initial price) in fixed time (we restrict our consideration to zero-coupon bonds only). Therefore, the owner can have fixed income. Typically, there are many different bonds on the market with different times of maturity, and they are actively traded, so the analysis of bonds is very important for applications. For the bond-and-stock market models introduced above, we refer to bonds as a riskfree investment similar to a cash account. For instance, it is typical for the Black-Scholes market model where the bank interest rate is supposed to be constant.

© 2007 Nikolai Dokuchaev Mathematical Finance 104 The last feature (iii) has explicit economical sense: there are many different bonds (since bonds with different maturities represent different assets) but their evolution depends on few factors only, and the main factors are the ones that describe the evolution of r(t). The multistock market model can be used as a model for a market with many different bonds (or fixed income securities). Assume that we are using a multistock market model described above as the model for bonds (i.e., Si(t) are the bond prices). Feature (iii) can be expressed as the condition that σij(t)≡0 for all j>n,=1,…, N, where n is the number of driving Wiener processes, N is the number of bonds, N>>n. It follows that the matrix a is degenerate. This is a very essential feature of the bond market.


pages: 269 words: 83,307

Young Money: Inside the Hidden World of Wall Street's Post-Crash Recruits by Kevin Roose

activist fund / activist shareholder / activist investor, Basel III, cognitive dissonance, collateralized debt obligation, Credit Default Swap, credit default swaps / collateralized debt obligations, discounted cash flows, Donald Trump, East Village, eurozone crisis, fixed income, forward guidance, glass ceiling, Goldman Sachs: Vampire Squid, hedonic treadmill, jitney, knowledge worker, new economy, Occupy movement, plutocrats, Plutocrats, Robert Shiller, Robert Shiller, selection bias, shareholder value, side project, Silicon Valley, Skype, Steve Jobs, The Predators' Ball, too big to fail, urban planning, We are the 99%, young professional

But he’d never thought about the Martingale strategy as an interview question for a finance job. He talked through the possible outcomes and managed to convince the interviewer that he knew something about game theory and probability. Two weeks later, Samson got an e-mail telling him that he’d gotten an internship in Goldman’s fixed-income, currencies, and commodities division. Known as FICC, the division houses all of Goldman’s bond trading, mortgage sales, and other types of fixed-income transactions. It was also one of the most profitable areas of the firm, and accounted for anywhere from 50 to 70 percent of the entire firm’s revenue in a given year. In the moneymaking theater that was Goldman Sachs, he’d been invited to sit in the front row. That summer, Samson had crushed it. He had done his best rotation in mortgage sales, a top-tier desk with no shortage of competition among interns.

A life spent in constant go mode, and a career that consisted of subordinating her every worldly desire to other people—to these people, no less—was not what she wanted. Later that summer, I met Chelsea and several other analysts in her group at a bar in Murray Hill. It was pub quiz night, but none of them wanted to play. They were all more interested in gossiping about their third-year plans. Chelsea’s best friend at work, who worked in a related fixed-income group, said she’d be making at least $150,000, including her bonus, if she stayed for a third year. Another fixed-income analyst said he was going to try and re-up for a third year as well. But Chelsea, who rested her chin in her hand on the bar, couldn’t muster any enthusiasm at all. “I don’t mean to act like a rebel,” she said, “but I don’t want to stay.” The other analysts looked at her curiously. “I know I sound like an asshole,” she continued.

They had been recruited to work for one of the most prestigious firms on Wall Street, but now found themselves working for what they considered a lesser enterprise. To them, it was as if Tiffany had merged with Costco, and now they were stuck selling pristine jewels next to freezers of chicken cutlets. The new analysts spent four weeks in the ballroom of the Crowne Plaza, being put through their paces in a Finance 101 course that taught them the basics of equities, fixed income, corporate valuation, and other skills they would need for their jobs. Most of the job openings in the highly sought-after groups had been filled by Merrill kids. For the people who had originally been hired by Bank of America there were a few positions open in mortgage sales, a rate sales job or two, and a handful of openings in something called public finance. Of the open groups, Chelsea decided she liked mortgage sales the best.


pages: 350 words: 103,270

The Devil's Derivatives: The Untold Story of the Slick Traders and Hapless Regulators Who Almost Blew Up Wall Street . . . And Are Ready to Do It Again by Nicholas Dunbar

asset-backed security, bank run, banking crisis, Basel III, Black Swan, Black-Scholes formula, bonus culture, break the buck, buy and hold, capital asset pricing model, Carmen Reinhart, Cass Sunstein, collateralized debt obligation, commoditize, Credit Default Swap, credit default swaps / collateralized debt obligations, delayed gratification, diversification, Edmond Halley, facts on the ground, financial innovation, fixed income, George Akerlof, implied volatility, index fund, interest rate derivative, interest rate swap, Isaac Newton, John Meriwether, Kenneth Rogoff, Kickstarter, Long Term Capital Management, margin call, market bubble, money market fund, Myron Scholes, Nick Leeson, Northern Rock, offshore financial centre, Paul Samuelson, price mechanism, regulatory arbitrage, rent-seeking, Richard Thaler, risk tolerance, risk/return, Ronald Reagan, shareholder value, short selling, statistical model, The Chicago School, Thomas Bayes, time value of money, too big to fail, transaction costs, value at risk, Vanguard fund, yield curve, zero-sum game

Michael Sherwood had just become European head of FICC (fixed income, currencies, and commodities), perhaps Goldman’s least understood but most profitable division. Trading—derivatives in particular—was his forte. When credit derivatives were invented in the mid-1990s, Goldman held back. But once the utility of the new tools had been demonstrated, Sherwood became the firm’s leading default swap visionary. The newly invented tool was going to lead to the “derivatization of credit,” he would tell colleagues. He believed the market approach to buying, selling, and owning corporate bonds had a massive disadvantage to the much more transparent markets in equities. If you like the prospects of a company, say, Walmart, an equity trader only has to look at one type of security: Walmart’s stock. In fixed income, a company might have hundreds of different bonds in the market, repayable in different currencies, and with myriad maturity dates and interest payment profiles.

And a more dangerous place. For the Love of the Game When I first met Osman Semerci, in January 2007, he was beaming with pleasure. It was not just the $20 million bonus he had recently been awarded that caused him to glow with self-satisfaction as he flashed million-dollar smiles while sharing a celebratory dinner with a gaggle of his tuxedo-clad colleagues. As the dapper, Turkish-born head of fixed income, currencies, and commodities at Merrill Lynch cracked jokes, he was proudly clutching a phallic, hard-plastic trophy with the logo of the trade magazine I worked for honoring his firm as “House of the Year.” By this time, my professional life had become synced with the annual cycle of the bonus season. The financial trade press could not survive by publishing technical articles or by selling subscriptions and ads.

That led to the New York Fed and the OCC censuring the bank in July 2003, as part of a settlement in which it didn’t have to admit wrongdoing.23 Weill was forced to quit as chief executive (while remaining chairman).24 The incoming CEO, former general counsel Chuck Prince, may have seemed like a steady pair of hands on the wheel, but it was Prince who undermined the risk governance mechanism that Weill had put in place. Prince allowed Tom Maheras, the head of fixed income, to appoint his own risk managers. Feeling that his independence had been compromised, Sabatacakis quit in 2004 and was replaced by a Maheras crony, David Bushnell, whose first move was to abolish Sabatacakis’s trading book position limits.25 Hidden from public view, this weakening of internal risk governance made it ever more essential that Citi, the largest bank in the United States, was supervised properly.


pages: 349 words: 134,041

Traders, Guns & Money: Knowns and Unknowns in the Dazzling World of Derivatives by Satyajit Das

accounting loophole / creative accounting, Albert Einstein, Asian financial crisis, asset-backed security, beat the dealer, Black Swan, Black-Scholes formula, Bretton Woods, BRICs, Brownian motion, business process, buy and hold, buy low sell high, call centre, capital asset pricing model, collateralized debt obligation, commoditize, complexity theory, computerized trading, corporate governance, corporate raider, Credit Default Swap, credit default swaps / collateralized debt obligations, cuban missile crisis, currency peg, disintermediation, diversification, diversified portfolio, Edward Thorp, Eugene Fama: efficient market hypothesis, Everything should be made as simple as possible, financial innovation, fixed income, Haight Ashbury, high net worth, implied volatility, index arbitrage, index card, index fund, interest rate derivative, interest rate swap, Isaac Newton, job satisfaction, John Meriwether, locking in a profit, Long Term Capital Management, mandelbrot fractal, margin call, market bubble, Marshall McLuhan, mass affluent, mega-rich, merger arbitrage, Mexican peso crisis / tequila crisis, money market fund, moral hazard, mutually assured destruction, Myron Scholes, new economy, New Journalism, Nick Leeson, offshore financial centre, oil shock, Parkinson's law, placebo effect, Ponzi scheme, purchasing power parity, quantitative trading / quantitative finance, random walk, regulatory arbitrage, Right to Buy, risk-adjusted returns, risk/return, Satyajit Das, shareholder value, short selling, South Sea Bubble, statistical model, technology bubble, the medium is the message, the new new thing, time value of money, too big to fail, transaction costs, value at risk, Vanguard fund, volatility smile, yield curve, Yogi Berra, zero-coupon bond

Berkshire Hathaway’s annual meeting, an immense religious jamboree attended by adoring converts, is known as ‘Woodstock for Capitalists’. Buffet is the ‘Oracle of Omaha’. In 2003 Buffet took aim at derivatives, calling them ‘financial weapons of mass destruction’.1 He was joined in this crusade by a few notable figures. A significant fellow-traveller was Bill Gross, who managed PIMCO’s (one of the world’s largest investment management companies) vast fixed income fund. Their complaint seemed to be that derivative contracts had DAS_C02.QXP 8/7/06 20 4:22 PM Page 20 Tr a d e r s , G u n s & M o n e y hidden losses that would eventually emerge. This would affect the banks and insurance companies who traded in these instruments. They were concerned that derivatives allowed companies and investors to gamble with other people’s money. I had naïvely assumed that gambling with other people’s money was part and parcel of capitalism.

Fealty also depends on sordid unknown knowns: a compromising photo of the individual is helpful, as is knowledge of past financial indiscretions or cover ups. Occasional bloodletting is unavoidable. This takes the form of a random brutal execution of a formerly trusted associate for no plausible reason. It has no purpose other than to engender fear in the remaining followers. The major court game is ‘divide and conquer’, with the ruler playing their people off against each other. In one case, the head of fixed income promised his job to all seven lieutenants, simultaneously (I was one of those to whom the job was promised). It all ends in a palace coup d’état then the cycle just repeats itself. Uncivil wars Overlaps between units abound. One bank once espoused a Maoist philosophy – ‘Let many flowers bloom’. In the derivatives business, the bank at times ran numerous, parallel, overlapping portfolios. At one stage, there were dollar swap portfolios in New York, London, Tokyo, Toronto, DAS_C03.QXP 8/7/06 4:25 PM Page 69 2 N Beautiful lies – the ‘sell’ side 69 Frankfurt, Zurich, Hong Kong, Singapore and Sydney.

Tired of this game, Greg translated the side conversation. Nero is a large man, about as wide as he is tall; another of his nicknames was ‘slug’. The older man had been asking his colleague, ‘What did the big fat whale say?’ Perhaps the most embarrassing cross-cultural incident involved a trader visiting Japan. He thought it might be useful to have his business cards translated into Japanese. His official title was ‘Trader–Fixed Income’. The Japanese translation was ‘Trader on Fixed Salary’. The card brought strange looks from the bemused Japanese clients. It seemed more than a little was lost in translation. A day in the life Recently, I had lunch with Steve; we had known each other a long time; we had worked together and afterwards had kept in touch. ‘Maaateeeee,’ he began. ‘Mate’ or its affectionate counterpart ‘maaaate’ and ‘maaateeeee’ is a sign of Anglo-Saxon intimacy amongst traders.


Quantitative Trading: How to Build Your Own Algorithmic Trading Business by Ernie Chan

algorithmic trading, asset allocation, automated trading system, backtesting, Black Swan, Brownian motion, business continuity plan, buy and hold, compound rate of return, Edward Thorp, Elliott wave, endowment effect, fixed income, general-purpose programming language, index fund, John Markoff, Long Term Capital Management, loss aversion, p-value, paper trading, price discovery process, quantitative hedge fund, quantitative trading / quantitative finance, random walk, Ray Kurzweil, Renaissance Technologies, risk-adjusted returns, Sharpe ratio, short selling, statistical arbitrage, statistical model, survivorship bias, systematic trading, transaction costs

Stationarity is not limited to the spread between stocks: it can also be found in certain currency rates. For example, the Canadian dollar/Australian dollar (CAD/AUD) cross-currency rate is quite stationary, both being commodities currencies. Numerous pairs of futures as well as well as fixed-income instruments can be found to be cointegrating as well. (The simplest examples of cointegrating futures pairs are calendar spreads: long and short futures contracts of the same underlying commodity but different expiration months. Similarly for fixed-income instruments, one can long and short bonds by the same issuer but of different maturities.) FACTOR MODELS Financial commentators often say something like this: “The current market favors value stocks,” “The market is focusing on earnings growth,” or “Investors are paying attention to inflation numbers.”

(See discussions in Chapter 6 on this issue.) Since the actual returns distributions have fat tails, one should be quite wary of using too much leverage on normally low-beta stocks. SUMMARY This book has been largely about a particular type of quantitative trading called statistical arbitrage in the investment industry. Despite this fancy name, statistical arbitrage is actually far simpler than trading derivatives (e.g., options) or fixed-income instruments, both conceptually and mathematically. I have described a large part of the statistical arbitrageur’s standard arsenal: mean reversion and momentum, regime switching, stationarity and cointegration, arbitrage pricing theory or factor model, seasonal trading models, and, finally, high-frequency trading. P1: JYS c07 JWBK321-Chan September 24, 2008 Special Topics in Quantitative Trading 14:4 Printer: Yet to come 155 Some of the important points to note can be summarized here: r Mean-reverting regimes are more prevalent than trending regimes. r There are some tricky data issues involved with backtesting mean-reversion strategies: Outlier quotes and survivorship bias are among them. r Trending regimes are usually triggered by the diffusion of new information, the execution of a large institutional order, or “herding” behavior. r Competition between traders tends to reduce the number of mean-reverting trading opportunities. r Competition between traders tends to reduce the optimal holding period of a momentum trade. r Regime switching can sometimes be detected using a dataminingx approach with numerous input features. r A stationary price series is ideal for a mean-reversion trade. r Two or more nonstationary price series can be combined to form a stationary one if they are “cointegrating.” r Cointegration and correlation are different things: Cointegration is about the long-term behavior of the prices of two or more stocks, while correlation is about the short-term behavior of their returns. r Factor models, or arbitrage pricing theory, are commonly used for modeling how fundamental factors affect stock returns linearly. r One of the most well-known factor models is the Fama-French Three-Factor model, which postulates that stock returns are proportional to their beta and book-to-price ratio, and negatively to their market capitalizations. r Factor models typically have a relatively long holding period and long drawdowns due to regime switches. r Exit signals should be created differently for mean-reversion versus momentum strategies. r Estimation of the optimal holding period of a mean-reverting strategy can be quite robust, due to the Ornstein-Uhlenbeck formula.

Some of the ones I have used are: sum, cumsum, diag, max, min, mean, std, corrcoef, repmat, reshape, squeeze, sort, sortrow, rand, size, length, eigs, fix, round, floor, ceil, mod, factorial, setdiff, union, intersect, ismember, unique, any, all, eval, eye, ones, strmatch, regexp, regexprep, plot, hist, bar, scatter, try, catch, circshift, datestr, datenum, isempty, isfinite, isnan, islogical, randperm If the built-in functions of the basic MATLAB platform do not meet all your needs, you can always purchase additional toolboxes from MATLAB. Some of the toolboxes useful to quantitative traders are the optimization, partial differential equations P1: JYS app JWBK321-Chan 168 September 24, 2008 14:13 Printer: Yet to come APPENDIX (for derivative traders), genetic algorithms, statistics, neural networks, signal processing, wavelet, financial, financial derivatives, GARCH, financial times series, datafeed, and fixed-income toolboxes. If these toolboxes are too costly, or if they still do not meet all your needs, there are also a number of free user-contributed toolboxes available for download from the Internet. I have introduced one of them in this book: the Econometrics toolbox developed by James LeSage (www.spatial-econometrics.com). There are a number of others that I have used before: the Bayes Net toolbox from Kevin Murphy (www.cs.ubc.ca/∼murphyk/Software/BNT/bnt.html), or the GARCH toolbox from Kevin Sheppard (www.kevinsheppard. org/research/ucsd garch/ucsd garch.aspx).


pages: 43 words: 11,160

Best Places to Retire: The Top 15 Affordable Towns for Retirement on a Budget (Retirement Books) by Clayton Geoffreys

fixed income

We get used to having a stable source of income and cash inflow when we are still working and once we retire, all of that can change drastically. It's important that we make plans or a chart for our monthly or weekly expenses during retirement. Money can be depleted easily if all you do is spend without keeping a close watch. Be sure to list down all of your fixed expenses (groceries, food, rent, and taxes) based on your fixed income or asset. What Do You Do with Your Personal Savings? People immediately jump to the conclusion that their entire life savings are limitless, but unless you have invested some of your finances elsewhere, then there is a big chance that your life savings are going to run out in time. Instead, try to search for retirement savings accounts in your area. There are some accounts that are easier to set up especially if you are a small business owner.

When you start searching for a city, try to read what you can find about it and compare the city’s qualities to the ones you have written down. However, it does not stop there, because it’s best to look at other choices as you might be able to find a more suitable place than the one you are looking at right now. There are costs and expenses in everything so be sure to keep your savings and expenditures in check. It’s ideal to match your fixed income or fixed assets along with your fixed expenses to make sure that you will not fall into financial trouble. Also, when you withdraw money from your retirement savings, keep it at a diminutive amount, around 2% per annum or if you retired at a much later age like 70, you can increase it to 4% or 6% per annum. When you are deciding on which city you want to settle in, it’s best to look at the whole scenario as if you are searching for the right vacation ‘get away’, only that this time you are going to permanently settle there.


pages: 339 words: 95,270

Trade Wars Are Class Wars: How Rising Inequality Distorts the Global Economy and Threatens International Peace by Matthew C. Klein

Albert Einstein, Asian financial crisis, asset allocation, asset-backed security, Berlin Wall, Bernie Sanders, Branko Milanovic, Bretton Woods, British Empire, business climate, business cycle, capital controls, centre right, collective bargaining, currency manipulation / currency intervention, currency peg, David Ricardo: comparative advantage, deglobalization, deindustrialization, Deng Xiaoping, Donald Trump, Double Irish / Dutch Sandwich, Fall of the Berlin Wall, falling living standards, financial innovation, financial repression, fixed income, full employment, George Akerlof, global supply chain, global value chain, illegal immigration, income inequality, intangible asset, invention of the telegraph, joint-stock company, land reform, Long Term Capital Management, Malcom McLean invented shipping containers, manufacturing employment, Martin Wolf, mass immigration, Mikhail Gorbachev, money market fund, mortgage debt, New Urbanism, offshore financial centre, oil shock, open economy, paradox of thrift, passive income, reserve currency, rising living standards, Robert Shiller, Robert Shiller, Ronald Reagan, savings glut, Scramble for Africa, sovereign wealth fund, The Nature of the Firm, The Wealth of Nations by Adam Smith, Tim Cook: Apple, trade liberalization, Wolfgang Streeck

The total supply of U.S. corporate debt issued by nonfinancial companies grew by just $200 billion between the start of 2002 and the end of 2007, and most of that debt was issued at the end of the period. At the same time, pension funds and life insurers the world over needed to buy more fixed income to offset the growth of their long-term liabilities. Even without Asian and Middle Eastern reserve managers hoovering up every new U.S. Treasury bond and much of the debt issued by Fannie and Freddie, there would have been a fundamental shortage of safe assets relative to demand. The heightened demand for U.S. fixed income needed to be matched with a massive increase in American borrowing, but neither the American government nor its businesses were willing to participate. Fig. 6.3. “When the ducks are quacking, feed them” (value of residential mortgages held in private-label conduits, USD trillions).

The result was that subsidiaries of American multinationals located in corporate tax havens accumulated trillions of dollars of financial assets in the past two decades. From 1998 through 2017, American companies operating in the seven corporate tax havens “earned” and then “reinvested” more than $2.1 trillion of profits. Over the same period, American companies operating in the rest of the world earned and reinvested less than $1.5 trillion in profits—a difference of roughly $640 billion.38 Most of this money ended up back in the United States as fixed-income investments even though it was considered foreign for tax purposes. Company reports are transparent about this. Apple’s 2017 annual report describes how most of its financial assets are “held by foreign subsidiaries” yet invested in “dollar-denominated holdings.” Microsoft’s 2017 annual report says that its “investments are predominantly U.S. dollar-denominated securities” even though it also says that 96 percent of its financial assets are “held by our foreign subsidiaries and would be subject to material repatriation tax effect.”39 Between the start of 2012 and the end of 2017, U.S. companies reinvested about $1.2 trillion in the main corporate tax havens, according to the Bureau of Economic Analysis.

The republic received very little cash and had to return to the market fairly soon thereafter. The loan was a great success for investors and the capital markets, however, and the newly emerging international loan market subsequently took off. Bankers made very large profits on limited risk. British investors receiving 4 percent on their own government’s perpetual bonds were eager to purchase fixed income with 6 percent coupons at initial prices ranging from 80 percent to 84 percent of face value from a country that, as many promoters and journalists suggested, seemed really no different from the United States forty years earlier. The Colombian bond quickly traded up in the secondary market. Thanks to the success of the 1822 Colombian loan, several other sovereign borrowers came to market that year.


pages: 212 words: 70,224

How to Retire the Cheapskate Way by Jeff Yeager

asset allocation, car-free, employer provided health coverage, estate planning, financial independence, fixed income, Pepto Bismol, pez dispenser, rent control, ride hailing / ride sharing, risk tolerance, Ronald Reagan, Zipcar

Because I don’t write traditional personal finance books, I always feel compelled to give readers a few words of advance warning about what to expect. As I often say: I don’t write books about how to get rich; I write books about how to get happy, perhaps with what you already have. That seems to me to be the real key to enjoying life, particularly when it comes to enjoying retirement, when many will be living on a fixed income. So by way of warning, if you’re looking for a book about retirement investing—particularly magical ways to hatch an ostrich-size retirement nest egg overnight without working or planning for it—this isn’t that book. The good news is, most books written about retirement focus almost exclusively on investing, so go pick up one of those books instead. Of course, these days, a lot of those tomes should be reclassified from nonfiction to fiction, given the experience of countless folks like Doris and Chuck Wye, who followed their advice like a rooster chasing a hen around the barnyard, and with a similar outcome.

This is a simple example, but let’s say you have a preretirement income of $60,000 and—since you’re determined to become more of a cheapskate after you retire—you believe you can live on only 85 percent of that amount in retirement. That means you’ll need an annual income of $51,000 in your first year of retirement, with cost-of-living increases factored in going forward. Like nearly three-quarters of all Americans today, you’re not lucky enough to have a traditional pension provided by your employer(s), one that would guarantee you an income stream for life. Nor do you have any annuities to provide additional fixed income. So the only income other than what you draw from your 401(k) and other savings will be Social Security, which, based on your work history, you calculate will be about $1,700 per month, or $20,400 per year. That leaves a difference of $30,600 per year to be made up from your nest egg. Assuming you withdraw 3 percent annually from your nest egg, that means—you guessed it—you need roughly ONE MILLION DOLLARS ($1,020,000, to be exact) in retirement savings in order to generate the level of income the experts insist you’ll need to live on in retirement.

In response to an article I wrote on this topic in January 2012 for my “Cheap Talk” blog on the AARP website (http://​blog.​aarp.​org/​author/​jeffy​eager​ultimate​cheap​skate), there was strong agreement among most readers who commented on the question I asked: Are you becoming more frugal with age? Most respondents said yes, their non-healthcare-related spending has definitely decreased—even dramatically so—with age. The interesting thing, though, was some of the reasons, stories, and explanations readers gave regarding this phenomenon: “Yes, I am getting cheaper the older I get. I think I am getting ready to live on a fixed income.” (Wendy L. Dietze, 60) “I believe I have become more frugal with age, at least on some things. I bring my lunch to work and have my own coffeepot at work to brew my own instead of buying it anywhere. On the other hand, I have a daughter in a private kindergarten, a new car payment, and other bills that make me become more frugal on these sorts of things.” (Bill Camp, 39) “As a retired 63 year old female, I find spending my savings after a lifetime of frugality is really hard.


pages: 206 words: 70,924

The Rise of the Quants: Marschak, Sharpe, Black, Scholes and Merton by Colin Read

"Robert Solow", Albert Einstein, Bayesian statistics, Black-Scholes formula, Bretton Woods, Brownian motion, business cycle, capital asset pricing model, collateralized debt obligation, correlation coefficient, Credit Default Swap, credit default swaps / collateralized debt obligations, David Ricardo: comparative advantage, discovery of penicillin, discrete time, Emanuel Derman, en.wikipedia.org, Eugene Fama: efficient market hypothesis, financial innovation, fixed income, floating exchange rates, full employment, Henri Poincaré, implied volatility, index fund, Isaac Newton, John Meriwether, John von Neumann, Joseph Schumpeter, Kenneth Arrow, Long Term Capital Management, Louis Bachelier, margin call, market clearing, martingale, means of production, moral hazard, Myron Scholes, Paul Samuelson, price stability, principal–agent problem, quantitative trading / quantitative finance, RAND corporation, random walk, risk tolerance, risk/return, Ronald Reagan, shareholder value, Sharpe ratio, short selling, stochastic process, Thales and the olive presses, Thales of Miletus, The Chicago School, the scientific method, too big to fail, transaction costs, tulip mania, Works Progress Administration, yield curve

Mutual funds have been designed that contain an option component which trades off some of the return in exchange for an option protection in case the portfolio value drops below a threshold level. Indeed, in 1976, Merton and Scholes teamed up to create the world’s first such instrument in the USA, the Money Market/Options Fund. Options can also be used to protect against a declining yield on a fixed income security. Alternatively, an investor can book some profits immediately in the security by selling a call on a bond. If the bond price rises above a certain level, the seller of the call must sacrifice the underlying bond and in turn sacrifice the gain above the exercise price, but is able to book some profit with certainty. Assuming that these fixed-income options are properly priced in an efficient market, we can even calculate the implied volatility by solving the Black-Scholes equation for the volatility necessary to generate the prevailing price. This technique allows the Federal Reserve to measure point volatility in bond markets, or analysts to obtain a measure for the perceived level of volatility in a securities market.

Merton and Scholes collaborated on some of these studies, especially following Scholes’ return to the Sloan School. Both Merton and Scholes also supervised graduate students and consulted with mutual fund and investment houses part time. On many occasions, they had the chance to work with John Meriwether, the influential and successful investment director of Salomon Brothers, a significant employer of MIT finance graduates. The investment house’s proprietary algorithms for the trading of fixed-income securities employed Black-Scholes-Merton models that had been modified and extended in-house to earn arbitrage profits for Salomon Brothers. For ten years, from 1978 to 1987, Merton continued to explore issues of risk bearing and sharing, but increasingly from an institutional perspective. During this period, he served as the President of the American Finance Association, and explored measures of market efficiency.

He also received a Doctor of Management Science (Honoris Causa) degree from National Sun Yat-Sen University in 1998, a Doctor of Science (Honoris Causa) degree from the Athens 174 The Rise of the Quants University of Economics and Business in 2003, a Doctor Honoris Causa degree from the Universidad Nacional Mayor de San Marcos of Lima, Peru, a Doctor of Philosophy Honoris Causa degree from the Universidad Nacional Federico Villarreal, Lima, in 2004, and a Doctor of Science, Honoris Causa degree from Claremont Graduate University in California in 2008. Merton remains a member of the National Bureau of Economic Research and of the International Board of Scientific Advisers of the Tinbergen Institute. He serves on a number of advisory and editorial boards, including the Journal of Fixed Income, the Journal of Banking and Finance, and the Journal of Financial Education. He sits on the advisory boards of the European Finance Review, the International Journal of Theoretical and Applied Finance, Mathematical Finance, and the Review of Derivatives Research. Despite his exhilarating and ultimately historically painful experience with Long Term Capital Management, he remains the consummate scholar and academic.


Stock Market Wizards: Interviews With America's Top Stock Traders by Jack D. Schwager

Asian financial crisis, banking crisis, barriers to entry, beat the dealer, Black-Scholes formula, commodity trading advisor, computer vision, East Village, Edward Thorp, financial independence, fixed income, implied volatility, index fund, Jeff Bezos, John Meriwether, John von Neumann, locking in a profit, Long Term Capital Management, margin call, money market fund, Myron Scholes, paper trading, passive investing, pattern recognition, random walk, risk tolerance, risk-adjusted returns, short selling, Silicon Valley, statistical arbitrage, the scientific method, transaction costs, Y2K

The performance results you're referring to are for our equity and equity-linked trading strategies, which have formed the core of our proprietary trading activities since our start over eleven years ago. For a few years, though, we also traded a fixed income strategy. That strategy was qualitatively different from the equity-related strategies we'd historically employed and exposed us to fundamentally different sorts of risks. Although we initially made a lot of money on our fixed income trading, we experienced significant losses during the global liquidity crisis in late 1998, as was the case for most fixed income arbitrage traders during that period. While our losses were much smaller, in both percentage and absolute dollar terms, than those suffered by, for example, Long Term Capital Management, they were significant enough that we're no longer engaged in this sort of trading at all.

These funds have attempted to beat the S&P 500 by 1 percent or a few percent, but they have not been consistent. How do they try to do it? At one extreme, P1MCO buys S&P futures for the stock exposure and tries to provide the additional 100 basis points return by managing a fixed income portfolio. Sure, that would work if interest rates are stable or go down. But if interest rates rise, aren't they taking the risk of a loss on their bond portfolio? WIN-WIN INVEST! Yes, they definitely are. In effect, all they are really doing is taking the active manager risk in the fixed income market as opposed to the equity market. What other approaches have people used to try to consistently outperform the S&P 500 benchmark? Some people attempt to beat the S&P 500 by trying to pick the best stocks in each sector. They will balance their sector investments to match the S&P 500, but within each sector they will weight certain stocks more heavily than others.

"ten-bagger," i61 Thailand, 18 Thermolase, 46-47 ThcSlreet.com, 218 Thorpe, Ed, 266 3Com, 22 lick indicators, 107-1 1, 114, 312, 322 Time, 277 timc-and-sales log, 80 lips, stock, 6, 13-14, 20, 25, 72, 173, 176, 312 Tokyo Stock Exchange, 223 traders: athletes compared with, 285, 288, 289-90, 291, 297, 310 author's previous works on, 30, 77, I 70, 189, 197, 214-15,233 black, 127-28, 136-38 competitive edge of, 61-62, 144-45, 172, 177,203, 217-18, 225-26, 255-56, 301-2 conviction of, 27, 37-38, 48-49, 51, 52, 55, 57, 120-21, 126, 152, 167, 171, 174, 288-97, 302-3 decision-making by, 6, 13-14, 20. 21-22, 23, 25, 72,78, 173, 1 7 6 , 3 1 2 , 3 1 8 determination of, 28, 29, 31, 54, 125. 174-75, 186-87, 194, 203-4, 205, 208, 283-84,299, 303^1 discipline of, 72, 166, 167-68, 177, 186, 187, 202, 205, 208, 209, 292, 298 experience of, 28, 1 19-22. 195, 254-55, 300, 304, 308,314,317-18 fees of, 35, 55.275 flexibility of, 188,299-300 independence of, 22-23, 26-27, 57-58, 60-61, 93, 119-21,254-55,301,316, 326 instincts of, 5, 16, 27, 28, 71-72, 186, 188, 278-79, 286-87 lessons from, 298-326 novice, 67, 72,93-94. 183-86, 204, 218-19, 286-87, 308 patience of, 167-68, 176, 309-10 personality of, 29, 281, 285, 288-97, 298-99, 312-13, 314 style of, 183-84,2)8-20,281-83, 286-87 in teams, 282-83 whole-picture perspective o f , xiii-xiv women, 77, 88-89 see also specific trailers trading: as art vs. science, 61, 7i—72 "bond ratio," 110-11 capitalization for, 10, 114-19, 120. 142, 146, 147, 205, 207, 222, 303 "catapult," 110 charts for, 158, 181-83, 264-74 complexity of, 3 1 5 — 1 6 contests for, 97, 111, 118, 170 currency, 5, 9, 202-3 equity, 6, 144-45,257 fixed-income, 271 goals For, 296,297, 310 high-probability. 110, 116. 177. 1 7 8 , 2 1 6 - 1 7 . 2 1 9 , 255-56,307,316 leveraged, 47-48, 69-70, I 17, 174, 204, 222, 314-15 losses capped in, 179-80, 184, 187, 188 paper, 175 positions in, see positions, trading post-trade analysis of, 97, 109-10, 179-80, 185, 187-88, 218, 219, 300-301,314 research for, see research restrictions on, 21-22, 27-28, 8 1 , 118-22, 152-53, 166, 179-80 systems of, 169, 171-82, 189-206, 264-74 timing in, xiii, 85, 157-58, 162-63, 171, 185, 196, 217, 220, 231, 232, 239, 257, 284-85, 305, 308 unethical, 79-80, 84, 234-35 as vocation, 119-21,316 Trading in the "Lane (Kiev), 288-89 Trading Places, 277 Trading to Win (Kiev), 288 transaction costs, 134-35, 255 turbo indexing, 34 TV set-type adjustments, 233-34 INDEX Ultrafem, 69 U.S.


Work Less, Live More: The Way to Semi-Retirement by Robert Clyatt

asset allocation, backtesting, buy and hold, delayed gratification, diversification, diversified portfolio, employer provided health coverage, estate planning, Eugene Fama: efficient market hypothesis, financial independence, fixed income, future of work, index arbitrage, index fund, lateral thinking, Mahatma Gandhi, McMansion, merger arbitrage, money market fund, mortgage tax deduction, passive income, rising living standards, risk/return, Silicon Valley, Thorstein Veblen, transaction costs, unpaid internship, upwardly mobile, Vanguard fund, working poor, zero-sum game

And what remains after that can still be taxed mostly or completely in the lowest 10% or 15% income tax brackets. (See “Consider Whether Low Tax Brackets Apply,” below, for more on these attractive brackets.) 244 | Work Less, Live More What to Put in an IRA With the current 10% income tax rate and 5% capital gains tax rate, some of the traditional wisdom about what to put in an IRA is starting to look dated. Traditionally, people put fixed-income or high-dividend assets in IRAs to shelter them from higher tax rates. Although putting fixed income in the IRA still makes sense, if you are paying little or no income tax, you might consider an alternative strategy: Place your actively managed mutual funds in the IRA, as these funds will tend to throw off a bit more capital gains distributions—possibly even some short-term capital gains—that could cause an unplanned tax bite. Also, keep any directly owned Treasury Inflation-Protected Securities (TIPS) in your IRA to avoid annual tax on the principal adjustment, which is a unique feature of these bonds.

You can find it at www.vanguard.com. 166 | Work Less, Live More There are a few other high-caliber firms that view managing your money as a sacred trust. They offer plenty of sensible index, tax-efficient, and low-fee funds. They include: • Dimensional Fund Advisors (DFA): www.dfaus.com • T. Rowe Price: www.troweprice.com • Dodge & Cox: www.dodgeandcox.com • Pacific Management Company (Pimco), fixed income specialists, online at www.pimco.com, and • Capital Research, managers of the American Funds mutual fund series, at www.americanfunds.com. Investment Terminology Explained For many people, one of the mystifying things about the investment world is the strange language spoken there. Here are some simple definitions for common terms and strategies, along with some basic advice for building your own autopilot along Rational Investing principles.

TiP Don’t sell stocks in a panic. No matter what you do, don’t start selling equities to load back up on allegedly safe CDs or bonds. The Rational Investing portfolio (described in Chapter 3) is both conservative and quite likely to deliver gains over the long run. But one sure way to undermine the portfolio’s performance would be to make a panicky decision to sell stocks at their lows, putting the money into low-yielding fixed-income investments with no chance of long-run appreciation. Special Advice for Couples “How do you put up with him around the house?” My wife has heard this one more often than any other source of wonder or confusion over semi-retirement. The answer she always gives is that she barely sees me chapter 7 | Don’t Blow It | 319 any more during the day as each of us goes about our various activities.


pages: 447 words: 104,258

Mathematics of the Financial Markets: Financial Instruments and Derivatives Modelling, Valuation and Risk Issues by Alain Ruttiens

algorithmic trading, asset allocation, asset-backed security, backtesting, banking crisis, Black Swan, Black-Scholes formula, Brownian motion, capital asset pricing model, collateralized debt obligation, correlation coefficient, Credit Default Swap, credit default swaps / collateralized debt obligations, delta neutral, discounted cash flows, discrete time, diversification, fixed income, implied volatility, interest rate derivative, interest rate swap, margin call, market microstructure, martingale, p-value, passive investing, quantitative trading / quantitative finance, random walk, risk/return, Satyajit Das, Sharpe ratio, short selling, statistical model, stochastic process, stochastic volatility, time value of money, transaction costs, value at risk, volatility smile, Wiener process, yield curve, zero-coupon bond

Crossing by division: example (data June 06): hence, 1 USD = (1.5627/1.2622) CHF = 1.2381 CHF in mid. For a 2-pips spread, it gives: USD/CHF @ 1, 2380–1.2382. FURTHER READING Richard T. BAILLIE, Patrick C. McMAHON, The Foreign Exchange Market, Theory and Econometric Evidence, Cambridge University Press, 1990, 276 p. Patrick J. BROWN, Bond Markets: Structures and Yield Calculations, ISMA Publications, 1998, 96 p. Frank FABOZZI, The Handbook of Fixed Income Securities, McGraw-Hill, 7th ed., 2005, 1500 p. Frank FABOZZI, Fixed Income Mathematics, McGraw-Hill, 4th ed., 2005, 600 p. Imad A. MOOSA, Razzaque H. BHATTI, The Theory and Empirics of Exchange Rates, World Scientific Publishing Company, 2009, 512 p. Lucio SARNO, Mark TAYLOR, The Economics of Exchange Rates, Cambridge University Press, 2003, 330 p. Tim WEITHERS, Foreign Exchange, John Wiley & Sons, Inc., Hoboken, 2006, 336 p.

Darrell DUFFIE, Dynamic Asset Pricing Theory, Princeton University Press, 2001, 472 p. Darrell DUFFIE, Security Markets: Stochastic Models, Academic Press Inc, 1988, 250 p. E. ELTON, M. GRUBER, S. BROWN, W. GOETZMANN, Modern Portfolio Theory and Investments Analysis, John Wiley & Sons, Inc., Hoboken, 2006, 752 p. R.F. ENGLE, D.L. McFADDEN (eds) Handbook of Econometrics, Elsevier, 1994. Frank FABOZZI, The Handbook of Fixed Income Securities, McGraw-Hill, 7th ed., 2005, 1500 p. Frank FABOZZI, Fixed Income Mathematics, McGraw-Hill, 4th ed., 2005, 600 p. Frank J. FABOZZI, Anand K. BHATTACHARYA, William S. BERLINER, Mortgage-Backed Securities: Products, Structuring and Analytical Techniques, John Wiley & Sons, Inc., Hoboken, 2007, 336 p. Frank J. FABOZZI, Roland FUSS, Dieter G. KAISER, The Handbook of Commodity Investing, John Wiley & Sons, Inc., Hoboken, 2008, 986 p.

BIGLOVA, “Desirable properties of an ideal risk measure in portfolio theory”, International Journal of Theoretical and Applied Finance, 2005. 3 This third component can be viewed as the “correlation” term, in the calculation of a variance or standard deviation for two different assets (σP2 = w12 σ22 + w22 σ22 + 2ρw1w2σ1σ2), and expresses to what extent both impacts are more or less opportunely combined. 4 See for example Mathieu CUBILIE, “Fixed income attribution model”, The Journal of Performance Measurement, Winter 2005/2006, pp. 46–63. 5 This ratio is also called “Gamma”. 6 See for example A. BERNARDO, O. LEDOIT, “Gain, loss and asset pricing”, The Journal of Political Economy, Jan 2000, pp. 144–172. 7 This section is partly inspired from Philippe JORION, Financial Risk Manager Handbook, 5th ed., 2009, John Wiley & Sons, Inc., Hoboken, and Moorad CHOUDHRY, An Introduction to Value-at-Risk, 4th ed., 2006, John Wiley & Sons, Ltd, Chichester. 8 To make a more precise calculation, the width of the bins should be narrower than 0.5%, as used here. 9 The 2510 returns used for the example present a kurtosis of 7.81 and a skewness of −0.10. 10 In the initial basic example, the only risk factor was the price change of the exposure in S&P 500. 11 A.


The Fix: How Bankers Lied, Cheated and Colluded to Rig the World's Most Important Number (Bloomberg) by Liam Vaughan, Gavin Finch

asset allocation, asset-backed security, bank run, banking crisis, Bernie Sanders, Big bang: deregulation of the City of London, buy low sell high, call centre, central bank independence, collapse of Lehman Brothers, corporate governance, credit crunch, Credit Default Swap, eurozone crisis, fear of failure, financial deregulation, financial innovation, fixed income, interest rate derivative, interest rate swap, Kickstarter, light touch regulation, London Interbank Offered Rate, London Whale, mortgage debt, Northern Rock, performance metric, Ponzi scheme, Ronald Reagan, social intelligence, sovereign wealth fund, urban sprawl

He became a managing director before his 35th birthday, and by the time he left Morgan Stanley for Credit Suisse First Boston in 1992, he was running the bank’s European and Asian bond-trading operations. Diamond then moved his young family to Japan to become the Swiss bank’s chairman, president and CEO for Asia. He was soon promoted to head of fixed income and currencies globally and given a seat on the executive board in New York. In 1996, Barclays CEO Martin Taylor, an Eton and Oxford-educated former journalist, hired the 45-year-old Diamond to come to London and run the lender’s securities and investment division. By then fixed income,currencies and commodities,or FICC as it’s known in the industry, was driving profits at the bulge-bracket investment banks and Diamond was a rising star. One of his first moves was to sell the equities and merchant banking operations to concentrate on debt capital markets.

His colleagues included Tom Steyer, who would go on to start Farallon Capital Management; Eddie Lampert, who founded ESL Investments; and Richard Perry, the founder of Perry Capital. The three hedge-fund managers are now worth a combined $5 billion, according to Forbes magazine, leading Gensler to quip: “Maybe I should have stayed there.” Other alumni include Treasury Secretary Hank Paulson. A few years after making partner, Gensler was dispatched to Tokyo to run the fixed-income, currencies and commodities trading business. By then he was married to an Italian-American artist with an MBA from Columbia, Francesca Danieli, and the couple had two daughters under three years old. They lived in Roppongi, the same well-to-do neighborhood Tom Hayes would move to. About a third of the $300 million in Escape to London 73 revenue Gensler oversaw came from trading yen-based swaps, the very instruments Hayes and his counterparts bought and sold.

(Bob) xi, 90–1, 92, 94, 96–9, 134, 136, 137, 139–46, 170 Diamond, Robert Edward, Sr. 90, 93, 94 Dimon, Jamie 137 DKB Financial Products 17 Dole, Bob 127 Ducrot, Yvan 81, 82, 85, 86, 126 Dudley, William 51 Dynegy 41 easyJet 144 Engel, Marcy 17 Enrich, David 151 Enron 42, 70, 101, 116, 154 ESL Investments 72 Euribor 135–6 euro 54 eurodollar futures 17 European Banking Federation 135 European Central Bank (ECB) 99, 118 European Commission 118 eurozone debt crisis xi Ewan, John 50, 51–2, 161–2, 163 exchange-rate mechanism (EU) 54 Fannie Mae 103 Farallon Capital Management 72 197 Farmanfarmaian, Khodadad 13, 15, 18 Farr, Terry 30–2, 33, 37, 63, 64, 65, 68, 79, 85, 117, 148, 168, 169 Federal Bureau of Investigation (FBI) 125, 129 Federal Energy Regulatory Commission 41 Federal Reserve 45, 55, 167 Term Auction Facility (TAF) 55 Federal Reserve Bank 51 Financial Conduct Authority (FCA) 129, 168, 173 Financial Services Authority (FSA) 54, 56–60, 75, 105–8, 133, 137, 140–3, 148, 152, 159, 163 Financial Times 73, 141, 146 Finma 109, 110 fixed income,currencies and commodities (FICC) 91 floating-rate note 15 Flowers, Chris 72 Foreign Exchange and Money Markets Committee (FXMMC) 50–1, 56, 115, 163 forward rate agreements 10 Fraser, Simon 144 Freshfield Bruckhaus Deringer 107 FTSE 171 Fulcrum Chambers 148, 155 Galbraith, Evan 15 Garstangs Burrows Bussin 155 Geithner, Tim 54–5, 69, 70 Gensler, Francesca 70, 135 Gensler, Gary 69–75, 89, 91, 135, 136, 169 Great Mutual Fund Trap, The 72 Gensler, Robert 71–2 Ghosh, Dr.


pages: 289 words: 77,532

The Secret Club That Runs the World: Inside the Fraternity of Commodity Traders by Kate Kelly

Bakken shale, bank run, business cycle, Credit Default Swap, diversification, fixed income, Gordon Gekko, index fund, light touch regulation, locking in a profit, London Interbank Offered Rate, Long Term Capital Management, margin call, paper trading, peak oil, Ponzi scheme, risk tolerance, Ronald Reagan, side project, Silicon Valley, Sloane Ranger, sovereign wealth fund, supply-chain management, the market place

Morgan Stanley wasn’t alone there. Banks everywhere were relying on commodity traders to help them survive the rout in mortgage-backed securities and the resultant setbacks in other markets. At Goldman Sachs, which reported fixed-income revenues of $3.71 billion for that year and $22 billion overall, commodities contributed more than $3 billion. Even at other banks with smaller, less profitable commodities units, the trading of raw materials was a major help. Among the top ten investment banks, commodities on average made up 14 percent of their combined total fixed-income revenue. Morgan and Goldman tended to top the list, with Barclays, JPMorgan, Bank of America, and others following behind. Bank commodities units made money in three ways. The first was by helping corporations involved in the physical side of the commodities business to hedge their exposure to changing commodity prices.

In 1990, he advised the National Football League on the sale of its broadcast rights to television networks over the coming four years. (One of Gensler’s tactics, which involved withholding the rights to broadcast the 1994 Super Bowl, helped net the league a record $3.6 billion package.) He had also worked overseas, relocating in 1993 to Tokyo, where he ran the Asian branch of Goldman’s sprawling fixed-income, or bond, division. The job put him in close proximity to a major financial scandal: a series of futures contract trades at the Singapore office of the UK-based Barings Bank on the direction of the Japanese stock market and certain interest rates that ultimately brought Barings down. For Gensler, who knew little about such contract markets before living in Tokyo, it was an education in the perils of trading complex products across borders during times of market stress.

candle-wax trade: Javier Blas, “Commodities: Into the Spotlight,” Financial Times, April 10, 2011, with additional reporting by the author. 4. THE BANKS once used by the energy company Texaco: Elsa Brenner, “Morgan Stanley Seals Deal on Texaco Headquarters,” New York Times, March 31, 2002, http://www.nytimes.com/2002/03/31/nyregion/in-business-morgan-stanley-seals-deal-on-texaco-headquarters.html. after the terrorist attacks: Ibid. 14 percent of their combined total fixed-income revenue: “Coalition Index—2012,” Coalition Development Ltd., February 2013. a quarter of Goldman’s pretax income: Gregory Zuckerman and Susanne Craig, “To Weather Rocky Period, Goldman Makes Riskier Bets,” Wall Street Journal, December 17, 2002, http://online.wsj.com/news/articles/SB1040074780804862913. $4 billion in trading profits: Kate Kelly, “How Goldman Won Big on Mortgage Meltdown,” Wall Street Journal, December 14, 2007, http://online.wsj.com/news/articles/SB119759714037228585


pages: 244 words: 79,044

Money Mavericks: Confessions of a Hedge Fund Manager by Lars Kroijer

activist fund / activist shareholder / activist investor, Bernie Madoff, capital asset pricing model, corporate raider, diversification, diversified portfolio, family office, fixed income, forensic accounting, Gordon Gekko, hiring and firing, implied volatility, index fund, intangible asset, Jeff Bezos, Just-in-time delivery, Long Term Capital Management, merger arbitrage, NetJets, new economy, Ponzi scheme, post-work, risk-adjusted returns, risk/return, shareholder value, Silicon Valley, six sigma, statistical arbitrage, Vanguard fund, zero-coupon bond

London beckoned … and I was eager to follow my new calling. 2 * * * Taking the plunge Joining ‘The Firm’ HBK was founded in the early 1990s as a convertible arbitrage shop. Harlan Korenvaes had used his connections from heading the convertibles group at Merrill Lynch to raise money for his own venture. Since inception, the returns had been excellent. After the early days of focusing on one area, the firm had quickly expanded into others such as fixed-income arbitrage, merger arbitrage, emerging-markets fixed-income, and special situations. When I joined in July 1999 the firm was managing around $1.5 billion in assets, on its way to managing double-digit billions five years later. There were eight partners at the firm when I joined, along with a whole army of people in back offices for a total worldwide headcount of around 150. The firm made a point of being discreet about its existence – over the years I came across many people even inside the hedge-fund community who had never heard of HBK, although it ranked among the world’s largest and best-performing funds.

The general feedback from the guys (there were virtually no women in the crowd) was similar: their jobs were not very structured, there was little hierarchy, skill was enthusiastically acknowledged by superiors and lack of it punished mercilessly. The job was entrepreneurial, in that you were encouraged to pursue what you thought were interesting angles, and if you were good the money was great. It was also clear that the type of work varied quite a bit from fund to fund. While the fixed-income or statistical arbitrage funds could be very mathematical in nature, the work at some of the long or short funds largely resembled that of more traditional stock-picking. Joining the clan I eventually joined a value fund in New York called SC Fundamental. During the interview process, the firm’s founder, Peter Collery, had thoroughly impressed me and I still consider him one of the smartest people I have ever met.

Someone else sat down, but quickly excused himself when he saw a better table across the room with someone he knew. The evening was not looking like a breakthrough event for Holte, and I briefly considered going back to my room and ordering room service. Two middle-aged Asian-looking guys sat down and made typically formal introductions. At least they made an effort to be nice to the lonely no-hoper. But sadly I could hardly understand their heavily accented English. ‘Ah, start-up. Good. Good. Fixed income bad. Macro good,’ and so on. After establishing that they mainly invested in macro, and only in managers who had been running for three years, I realised that they would also rather talk to each other. So there I was as a social outcast who ended up drinking too much of the lovely red wine. Half-drunk and halfway through dessert, I excused myself to join some people who had retired to the terrace to smoke.


pages: 300 words: 77,787

Investing Demystified: How to Invest Without Speculation and Sleepless Nights by Lars Kroijer

Andrei Shleifer, asset allocation, asset-backed security, Bernie Madoff, bitcoin, Black Swan, BRICs, Carmen Reinhart, cleantech, compound rate of return, credit crunch, diversification, diversified portfolio, equity premium, estate planning, fixed income, high net worth, implied volatility, index fund, intangible asset, invisible hand, Kenneth Rogoff, market bubble, money market fund, passive investing, pattern recognition, prediction markets, risk tolerance, risk/return, Robert Shiller, Robert Shiller, selection bias, sovereign wealth fund, too big to fail, transaction costs, Vanguard fund, yield curve, zero-coupon bond

Things are slowly getting better and the next decade will see further expansion in the amount of fixed-income products available for the retail investor. The historical indices that do go back some time have a heavy US bias and until recently broad-based indices were hard to come by, much less ones you could actually create as a product. Table 7.2 shows the performance data for some broad bond indices. Although the time period shown in Table 7.2 is far too short to make meaningful conclusions, 2008 stands out as an interesting data point. Both the US aggregate and global government bond indices had positive returns in a terrible equity market. The outperformance of highly rated bonds in a tough market environment points to the potential advantage of adding fixed income to the rational portfolio. As equity markets collapsed, investors sought security in highly rated bonds.

Like anything in the area of tax, clear these with a tax adviser, just to ensure that changes in rules have not rendered any of them ineffective or illegal. Different accounts Many investors will have different accounts that in aggregate add up to their investment portfolio. One may be a fully taxed normal deposit account whereas another is tax-free (e.g. a UK ISA). Generally, different accounts may have different tax characteristics; by putting the high-income generating investments (typically fixed income) in the tax-free accounts you may lower your overall tax burden. Being informed about which investments fit best into various accounts can save you taxes. In the UK, for example, if you pay tax it almost always make sense to have an ISA account and benefit from its tax advantages. Tax efficient proxies In some countries certain government bonds are tax advantageous. For example, in the US certain municipal bonds are exempt from certain taxes.

Fee-chasing advisers and banks sometimes neglect to push them to you (there aren’t enough fees for them to get a cut), suggesting that they are definitely worth looking at! ETFs have grown massively in prominence over the past couple of decades. In the mid-1990s they were still a fairly limited asset class, but in the early part of the following decade they exploded in number and size. There are today almost $2 trillion invested in ETFs, mainly in equity-related products, but increasingly in fixed-income funds. The assets are spread among literally thousands of different ETFs and you can use them to buy exposures to anything from the various standard indices, to volatility indices, gold bars, oil, sectors and more. This array of offerings is a good thing for the wider investor. It used to be practically very difficult for most investors to buy direct exposure to something like gold or oil without buying a gold mining or oil company stock.


pages: 421 words: 128,094

King of Capital: The Remarkable Rise, Fall, and Rise Again of Steve Schwarzman and Blackstone by David Carey

activist fund / activist shareholder / activist investor, asset allocation, banking crisis, Bonfire of the Vanities, business cycle, carried interest, collateralized debt obligation, corporate governance, corporate raider, credit crunch, diversification, diversified portfolio, fixed income, Gordon Gekko, margin call, Menlo Park, mortgage debt, new economy, Northern Rock, risk tolerance, Rod Stewart played at Stephen Schwarzman birthday party, Sand Hill Road, sealed-bid auction, Silicon Valley, sovereign wealth fund, The Predators' Ball, éminence grise

But Schwarzman and Peterson had from the start hoped to launch affiliated investment businesses and thought Fink was the ideal choice to head a new group focused on fixed-income investments—the Wall Street term for bonds and other interest-paying securities. They accepted Fink’s explanation that flawed computer software and bad data inputs had triggered the stunning trading losses, and they were further reassured by a conversation Schwarzman had with Bruce Wasserstein, First Boston’s cohead of M&A, who had become a friend and frequent tennis partner of Schwarzman’s. “Bruce told me that Larry was by far the most gifted person at First Boston,” Schwarzman says. Peterson and Schwarzman offered Fink a $5 million credit line to start a joint venture called Blackstone Financial Management, or BFM, which would trade in mortgage and other fixed-income securities. In exchange for the seed money, Blackstone’s partners got a 50 percent stake in the new business while Fink and his team, which included Ralph Schlosstein, a former Lehman partner and a good friend of Roger Altman’s, owned the other 50 percent.

Smith Barney and Harris Upham and Company had dumped him and his crew after they suffered massive losses in the October 1987 stock market crash. Overall, though, his record sparkled. From February 1983 to September 1987 at Smith Barney and then from May 1988 to March 1989 at Drexel, McVeigh’s arbitrage funds had returned on average 39 percent a year. Blackstone formed a joint venture with McVeigh along the lines of the one it had formed with Larry Fink for the fixed-income investment affiliate. McVeigh and his group were allotted a 50 percent interest in Blackstone Capital Arbitrage and were handed custody of about $50 million of Nikko’s money and were told to go at it. Blackstone couldn’t have picked a worse moment to ramp up in arbitrage. The economy was just beginning to slow, putting the brakes on takeovers, and by October 1989 LBOs and most takeover activity had screeched to a halt.

“There is no one who ever got a scintilla of equity in Blackstone who didn’t feel like it was pulling teeth from Steve. He’s not one of these people who graciously hands out equity,” the same former partner says. In January 1993, when Altman took a job as deputy treasury secretary in the new Clinton administration, he locked horns again with Schwarzman and Peterson over money. The issue this time was Altman’s potentially valuable 3 percent stake in Blackstone Financial Management, the fast-growing fixed-income venture that Larry Fink led. Altman fought tenaciously to hang on to his share of BFM, but Blackstone’s founders said no because of the potential conflict of interest. For a high-level Treasury Department official to own a sizable piece of a firm that traded Treasury securities would flunk just about any smell test. Altman’s exit from Washington in 1994 was even bumpier. That August he resigned under pressure over his handling of congressional inquiries into Whitewater—a financial and political scandal that grew out of a dubious 1980s Arkansas land deal involving Bill and Hillary Clinton.


pages: 431 words: 132,416

No One Would Listen: A True Financial Thriller by Harry Markopolos

backtesting, barriers to entry, Bernie Madoff, buy and hold, call centre, centralized clearinghouse, correlation coefficient, diversified portfolio, Edward Thorp, Emanuel Derman, Eugene Fama: efficient market hypothesis, family office, financial thriller, fixed income, forensic accounting, high net worth, index card, Long Term Capital Management, Louis Bachelier, offshore financial centre, Ponzi scheme, price mechanism, quantitative trading / quantitative finance, regulatory arbitrage, Renaissance Technologies, risk-adjusted returns, risk/return, rolodex, Sharpe ratio, statistical arbitrage, too big to fail, transaction costs, your tax dollars at work

As I was to learn over the next few years, the SEC had been created to monitor the stock market and it really had never evolved with the industry. Its investigators had neither the experience nor the training to understand something fairly complicated like fixed income, for example, an array of investments that yields a specific return on a regular basis but is much more complex than it initially appears. Municipal bonds, for example, is an area in which there is well-known and widespread corruption. And if the SEC couldn’t do the math for fixed income, it certainly could not do it for complicated derivatives or structured products. Structured products are combinations of underlying assets, like stocks and bonds, combined with various types of derivatives. They are incredibly complex. The SEC certainly doesn’t understand them; in fact, a lot of people on Wall Street don’t really understand them, so what chance does an individual investor have?

But in the early 1990s we were managing slightly more than a billion dollars. And that’s when a billion dollars was a lot of money. We considered ourselves an asset management firm, but we operated as a hedge fund. Because we were so small, each of us had to wear many hats, which was a great opportunity for me. I did everything there from routine correspondence, monthly client statements, and handling of compliance issues to assisting a very good fixed-income portfolio manager. It was a lot of grunt work, but I was in on all the action. I got to learn the business of being a money manager by being an assistant portfolio manager. I learned more there in three years than I might have learned elsewhere in a decade. Certainly one of the more important things I learned was that the numbers can be deceiving. There is a logic to mathematics, but there is also the underlying human element that must be considered.

The industry knew, there’s no question about that. After Madoff collapsed, I was told so many stories about people who knew he was a fraud and warned others. For example, I’ve been told about an e-mail a manager at one of the largest investment houses sent to a Madoff client in 2005, warning him that “everybody here knows Madoff is a fraud” and urging him to get his funds out. Another very smart guy Neil and I knew ran a fixed income arbitrage strategy for one of the major feeder funds that was heavily invested in Madoff. This manager joined the firm long after it had made its initial investments in Bernie, and I believe he eventually became a partner. This person is very outspoken, but he knows what he’s talking about. He speaks numbers. For example, when Rampart was marketing the product I’d created, he’d looked at it and figured out almost immediately that “This is a trade; it’s not a strategy.”


Mastering Private Equity by Zeisberger, Claudia,Prahl, Michael,White, Bowen, Michael Prahl, Bowen White

asset allocation, backtesting, barriers to entry, Basel III, business process, buy low sell high, capital controls, carried interest, commoditize, corporate governance, corporate raider, correlation coefficient, creative destruction, discounted cash flows, disintermediation, disruptive innovation, distributed generation, diversification, diversified portfolio, family office, fixed income, high net worth, information asymmetry, intangible asset, Lean Startup, market clearing, passive investing, pattern recognition, performance metric, price mechanism, profit maximization, risk tolerance, risk-adjusted returns, risk/return, shareholder value, Sharpe ratio, Silicon Valley, sovereign wealth fund, statistical arbitrage, time value of money, transaction costs

This also allows a firm to maintain stable operations, employ an investment team and maximize the efficiency of its resources. Exhibit 1.5 shows the lifecycle of a successful PE firm with a family of four funds. Exhibit 1.5 Lifecycle of a Successful PE Firm The LP Perspective Committing Capital and Earning Returns Investors have traditionally allocated capital to PE due to its historical outperformance of more traditional asset classes such as public equity and fixed income.16 However, this outperformance comes with higher (or rather different) risks first and foremost due to the illiquid nature of PE investments. Given its lack of liquidity and the long investment horizon of a PE fund, hitting a target allocation to PE is a far more challenging task than maintaining a stable allocation to any of the liquid asset classes.17 In addition, PE funds’ multiyear lock-up and 10-day notice period for capital calls introduce complex liquidity management questions.

To execute these successfully, an investor needs to develop a clear mandate and performance target for its PE program and set up an internal process for manager selection and portfolio management, all of which we discuss in this chapter. Deciding on an Allocation to PE Let’s start with a hypothetical LP, a large institutional investor such as a pension plan or endowment, which has been investing in global markets for decades—but only through public equity and fixed income. While it has used external fund managers and been willing to explore innovative tools, including derivatives, to date it has not added PE to its portfolio. Its investment committee (IC) has decided to give this fast-growing and, at first glance, attractive asset class serious consideration and is lining up the arguments in favor of and against such a move; needless to say, the IC must consider the risk of not allocating to PE and thereby depriving its beneficiaries of attractive future returns.

While this may be the case for developed markets, the argument fails when building exposure to the world’s global growth or emerging markets. Public exchanges in emerging markets only capture a portion of the overall economy and are often underweight with respect to a large number of interesting growth sectors. A PE fund’s investments in private companies provide a way to gain exposure to these sectors. Challenges of Investing in the PE Asset Class Introducing PE into a traditional portfolio of public equity and fixed income investments presents LPs with a novel set of challenges. These primarily relate to implementation, due to the specific characteristics of PE investing, including illiquidity, cash flow management, and organizational challenges. We look at each below. ILLIQUIDITY: PE demands a long-term commitment from its investors and a high comfort level with illiquidity; the required 10-year commitment of capital to a PE fund is necessary to execute its investment strategy, be it venture, growth or buyout.


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Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization: The Ideal Risk, Uncertainty, and Performance Measures by Frank J. Fabozzi

algorithmic trading, Benoit Mandelbrot, capital asset pricing model, collateralized debt obligation, correlation coefficient, distributed generation, diversified portfolio, fixed income, index fund, Louis Bachelier, Myron Scholes, p-value, quantitative trading / quantitative finance, random walk, risk-adjusted returns, short selling, stochastic volatility, Thomas Bayes, transaction costs, value at risk

DECOMPOSITION OF TIME SERIES REPRESENTATION OF TIME SERIES WITH DIFFERENCE EQUATIONS APPLICATION: THE PRICE PROCESS CONCEPTS EXPLAINED IN THIS CHAPTER (IN ORDER OF PRESENTATION) PART Two - Basic Probability Theory CHAPTER 8 - Concepts of Probability Theory HISTORICAL DEVELOPMENT OF ALTERNATIVE APPROACHES TO PROBABILITY SET OPERATIONS AND PRELIMINARIES PROBABILITY MEASURE RANDOM VARIABLE CONCEPTS EXPLAINED IN THIS CHAPTER (IN ORDER OF PRESENTATION) CHAPTER 9 - Discrete Probability Distributions DISCRETE LAW BERNOULLI DISTRIBUTION BINOMIAL DISTRIBUTION HYPERGEOMETRIC DISTRIBUTION MULTINOMIAL DISTRIBUTION POISSON DISTRIBUTION DISCRETE UNIFORM DISTRIBUTION CONCEPTS EXPLAINED IN THIS CHAPTER (IN ORDER OF PRESENTATION) CHAPTER 10 - Continuous Probability Distributions CONTINUOUS PROBABILITY DISTRIBUTION DESCRIBED DISTRIBUTION FUNCTION DENSITY FUNCTION CONTINUOUS RANDOM VARIABLE COMPUTING PROBABILITIES FROM THE DENSITY FUNCTION LOCATION PARAMETERS DISPERSION PARAMETERS CONCEPTS EXPLAINED IN THIS CHAPTER (IN ORDER OF PRESENTATION) CHAPTER 11 - Continuous Probability Distributions with Appealing Statistical Properties NORMAL DISTRIBUTION CHI-SQUARE DISTRIBUTION STUDENT’S t-DISTRIBUTION F-DISTRIBUTION EXPONENTIAL DISTRIBUTION RECTANGULAR DISTRIBUTION GAMMA DISTRIBUTION BETA DISTRIBUTION LOG-NORMAL DISTRIBUTION CONCEPTS EXPLAINED IN THIS CHAPTER (IN ORDER OF PRESENTATION) CHAPTER 12 - Continuous Probability Distributions Dealing with Extreme Events GENERALIZED EXTREME VALUE DISTRIBUTION GENERALIZED PARETO DISTRIBUTION NORMAL INVERSE GAUSSIAN DISTRIBUTION α-STABLE DISTRIBUTION CONCEPTS EXPLAINED IN THIS CHAPTER (IN ORDER OF PRESENTATION) CHAPTER 13 - Parameters of Location and Scale of Random Variables PARAMETERS OF LOCATION PARAMETERS OF SCALE CONCEPTS EXPLAINED IN THIS CHAPTER (IN ORDER OF PRESENTATION) CHAPTER 14 - Joint Probability Distributions HIGHER DIMENSIONAL RANDOM VARIABLES JOINT PROBABILITY DISTRIBUTION MARGINAL DISTRIBUTIONS DEPENDENCE COVARIANCE AND CORRELATION SELECTION OF MULTIVARIATE DISTRIBUTIONS CONCEPTS EXPLAINED IN THIS CHAPTER (IN ORDER OF PRESENTATION) CHAPTER 15 - Conditional Probability and Bayes’ Rule CONDITIONAL PROBABILITY INDEPENDENT EVENTS MULTIPLICATIVE RULE OF PROBABILITY BAYES’ RULE CONDITIONAL PARAMETERS CONCEPTS EXPLAINED IN THIS CHAPTER (IN ORDER OF PRESENTATION) CHAPTER 16 - Copula and Dependence Measures COPULA ALTERNATIVE DEPENDENCE MEASURES CONCEPTS EXPLAINED IN THIS CHAPTER (IN ORDER OF PRESENTATION) PART Three - Inductive Statistics CHAPTER 17 - Point Estimators SAMPLE, STATISTIC, AND ESTIMATOR QUALITY CRITERIA OF ESTIMATORS LARGE SAMPLE CRITERIA MAXIMUM LIKEHOOD ESTIMATOR EXPONENTIAL FAMILY AND SUFFICIENCY CONCEPTS EXPLAINED IN THIS CHAPTER (IN ORDER OF PRESENTATION) CHAPTER 18 - Confidence Intervals CONFIDENCE LEVEL AND CONFIDENCE INTERVAL CONFIDENCE INTERVAL FOR THE MEAN OF A NORMAL RANDOM VARIABLE CONFIDENCE INTERVAL FOR THE MEAN OF A NORMAL RANDOM VARIABLE WITH UNKNOWN VARIANCE CONFIDENCE INTERVAL FOR THE VARIANCE OF A NORMAL RANDOM VARIABLE CONFIDENCE INTERVAL FOR THE VARIANCE OF A NORMAL RANDOM VARIABLE WITH UNKNOWN MEAN CONFIDENCE INTERVAL FOR THE PARAMETER P OF A BINOMIAL DISTRIBUTION CONFIDENCE INTERVAL FOR THE PARAMETER λ OF AN EXPONENTIAL DISTRIBUTION CONCEPTS EXPLAINED IN THIS CHAPTER (IN ORDER OF PRESENTATION) CHAPTER 19 - Hypothesis Testing HYPOTHESES ERROR TYPES QUALITY CRITERIA OF A TEST EXAMPLES CONCEPTS EXPLAINED IN THIS CHAPTER (INORDER OF PRESENTATION) PART Four - Multivariate Linear Regression Analysis CHAPTER 20 - Estimates and Diagnostics for Multivariate Linear Regression Analysis THE MULTIVARIATE LINEAR REGRESSION MODEL ASSUMPTIONS OF THE MULTIVARIATE LINEAR REGRESSION MODEL ESTIMATION OF THE MODEL PARAMETERS DESIGNING THE MODEL DIAGNOSTIC CHECK AND MODEL SIGNIFICANCE APPLICATIONS TO FINANCE CONCEPTS EXPLAINED IN THIS CHAPTER (IN ORDER OF PRESENTATION) CHAPTER 21 - Designing and Building a Multivariate Linear Regression Model THE PROBLEM OF MULTICOLLINEARITY INCORPORATING DUMMY VARIABLES AS INDEPENDENT VARIABLES MODEL BUILDING TECHNIQUES CONCEPTS EXPLAINED IN THIS CHAPTER (IN ORDER OF PRESENTATION) CHAPTER 22 - Testing the Assumptions of the Multivariate Linear Regression Model TESTS FOR LINEARITY ASSUMED STATISTICAL PROPERTIES ABOUT THE ERROR TERM TESTS FOR THE RESIDUALS BEING NORMALLY DISTRIBUTED TESTS FOR CONSTANT VARIANCE OF THE ERROR TERM (HOMOSKEDASTICITY) ABSENCE OF AUTOCORRELATION OF THE RESIDUALS CONCEPTS EXPLAINED IN THIS CHAPTER (IN ORDER OF PRESENTATION) APPENDIX A - Important Functions and Their Features APPENDIX B - Fundamentals of Matrix Operations and Concepts APPENDIX C - Binomial and Multinomial Coefficients APPENDIX D - Application of the Log-Normal Distribution to the Pricing of Call Options References Index The Frank J. Fabozzi Series Fixed Income Securities, Second Edition by Frank J. Fabozzi Focus on Value: A Corporate and Investor Guide to Wealth Creation by James L. Grant and James A. Abate Handbook of Global Fixed Income Calculations by Dragomir Krgin Managing a Corporate Bond Portfolio by Leland E. Crabbe and Frank J. Fabozzi Real Options and Option-Embedded Securities by William T. Moore Capital Budgeting: Theory and Practice by Pamela P. Peterson and Frank J. Fabozzi The Exchange-Traded Funds Manual by Gary L. Gastineau Professional Perspectives on Fixed Income Portfolio Management, Volume 3 edited by Frank J. Fabozzi Investing in Emerging Fixed Income Markets edited by Frank J. Fabozzi and Efstathia Pilarinu Handbook of Alternative Assets by Mark J.

Fabozzi and Harry M. Markowitz Foundations of Economic Value Added, Second Edition by James L. Grant Financial Management and Analysis, Second Edition by Frank J. Fabozzi and Pamela P. Peterson Measuring and Controlling Interest Rate and Credit Risk, Second Edition by Frank J. Fabozzi, Steven V. Mann, and Moorad Choudhry Professional Perspectives on Fixed Income Portfolio Management, Volume 4 edited by Frank J. Fabozzi The Handbook of European Fixed Income Securities edited by Frank J. Fabozzi and Moorad Choudhry The Handbook of European Structured Financial Products edited by Frank J. Fabozzi and Moorad Choudhry The Mathematics of Financial Modeling and Investment Management by Sergio M. Focardi and Frank J. Fabozzi Short Selling: Strategies, Risks, and Rewards edited by Frank J. Fabozzi The Real Estate Investment Handbook by G.

Professor Fabozzi is a Fellow of the International Center for Finance at Yale university and on the Advisory Council for the Department of Operations Research and Financial Engineering at Princeton university. He is the editor of the Journal of Portfolio Management and an associate editor of Quantitative Finance. He is a trustee for the BlackRock family of closed-end funds. In 2002, he was inducted into the Fixed Income Analysts Society’s Hall of Fame and is the 2007 recipient of the C. Stewart Sheppard Award given by the CFA Institute. His recently coauthored books published by Wiley include Institutional Investment Management (2009), Quantitative Equity Investing (2010), Bayesian Methods in Finance (2008), Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization: The Ideal Risk, Uncertainty, and Performance Measures (2008), Financial Modeling of the Equity Market: From CAPM to Cointegration (2006), Robust Portfolio Optimization and Management (2007), and Financial Econometrics: From Basics to Advanced Modeling Techniques (2007).


pages: 416 words: 106,532

Cryptoassets: The Innovative Investor's Guide to Bitcoin and Beyond: The Innovative Investor's Guide to Bitcoin and Beyond by Chris Burniske, Jack Tatar

Airbnb, altcoin, asset allocation, asset-backed security, autonomous vehicles, bitcoin, blockchain, Blythe Masters, business cycle, business process, buy and hold, capital controls, Carmen Reinhart, Clayton Christensen, clean water, cloud computing, collateralized debt obligation, commoditize, correlation coefficient, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, disintermediation, distributed ledger, diversification, diversified portfolio, Donald Trump, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, fiat currency, financial innovation, fixed income, George Gilder, Google Hangouts, high net worth, Jeff Bezos, Kenneth Rogoff, Kickstarter, Leonard Kleinrock, litecoin, Marc Andreessen, Mark Zuckerberg, market bubble, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, Network effects, packet switching, passive investing, peer-to-peer, peer-to-peer lending, Peter Thiel, pets.com, Ponzi scheme, prediction markets, quantitative easing, RAND corporation, random walk, Renaissance Technologies, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Shiller, Ross Ulbricht, Satoshi Nakamoto, Sharpe ratio, Silicon Valley, Simon Singh, Skype, smart contracts, social web, South Sea Bubble, Steve Jobs, transaction costs, tulip mania, Turing complete, Uber for X, Vanguard fund, WikiLeaks, Y2K

For instance, the American Association of Individual Investors provides simplified models for three types of investors:4 • Aggressive investors: 90 percent diversified stock and 10 percent fixed income • Moderate investors: 70 percent diversified stock and 30 percent fixed income • Conservative investors: 50 percent diversified stock and 50 percent fixed income These three simple models can be used by people of different ages who have different investment time horizons. A whole host of equities can be included within “diversified stock,” and even more so for the variety of bonds that can be used for “fixed income.” For example, equities can be considered based on the size of the company, the growth characteristics, the valuation, the sector type, geographic exposure, and so on. Similarly, bonds can include government or corporate issues, with varying durations, credit ratings, and tax advantages.

CryptoCompare, Log scale. 8. https://www.wired.com/2017/01/monero-drug-dealers-cryptocurrency-choice-fire/. 9. http://www.coindesk.com/chinas-central-bank-issues-warnings-major-bitcoin-exchanges/. 10. An example of increased regulation dampening liquidity and trading volume is the new regulation that came out after the financial crisis of 2008. Regulations like Dodd-Frank required much stricter compliance processes, and led to decreased trading volumes especially in the fixed-income market. 11. http://www.nytimes.com/2013/12/06/business/international/china-bars-banks-from-using-bitcoin.html. 12. https://www.cryptocompare.com/coins/eth/analysis/BTC?type=Currencies. 13. Technically, it is absolute returns minus the risk-free rate, which is commonly represented by the three-month Treasury bill. 14. We’ll discuss the various investment options in the capital markets for investors in Chapter 15. 15. https://www.washingtonpost.com/news/wonk/wp/2017/01/03/why-bitcoin-just-had-an-amazing-year/?


pages: 162 words: 50,108

The Little Book of Hedge Funds by Anthony Scaramucci

Andrei Shleifer, asset allocation, Bernie Madoff, business process, carried interest, corporate raider, Credit Default Swap, diversification, diversified portfolio, Donald Trump, Eugene Fama: efficient market hypothesis, fear of failure, fixed income, follow your passion, Gordon Gekko, high net worth, index fund, John Meriwether, Long Term Capital Management, mail merge, margin call, mass immigration, merger arbitrage, money market fund, Myron Scholes, NetJets, Ponzi scheme, profit motive, quantitative trading / quantitative finance, random walk, Renaissance Technologies, risk-adjusted returns, risk/return, Ronald Reagan, Saturday Night Live, Sharpe ratio, short selling, Silicon Valley, Thales and the olive presses, Thales of Miletus, the new new thing, too big to fail, transaction costs, Vanguard fund, Y2K, Yogi Berra, zero-sum game

They search for discrepancies in the values of closely related securities (securities that tend to move in the same direction at the same time) so that they may take advantage of price differentials by simultaneously buying and selling them. In other words, pair traders search for situations where two companies in the same industry—or even two companies in different industries—may move in opposite directions. As a result of this practice, investors profit from the “relative value” of the two securities. Strategies within this classification include: Convertible Bond Arbitrage Fixed-Income Arbitrage Equity Market Neutral Relative value funds can pair trade indices, futures, options, currencies, and commodities; however, stocks that are in the same industry and have similar trading histories are most often used in this strategy. In my humble opinion, the pairs trading process is one of the most fascinating forms of hedge fund investing; however, it may also be the most nuanced.

What hedge fund strategies do you use? We engage in active trading strategies in long-short relative value trades. These strategies focus on alpha generation. We also take sector betas that are attractively priced and hard to source in a typical long only structure. 4. What do you see as the future of the industry? The future for active management is quite bright. Given the low absolute level of interest rates, fixed income returns will remain quite low, while the high volatility and lack of directionality in equity markets make long only strategies less effective. However, managers who mainly take a long only strategy and call it a hedge fund to justify higher fees may see attrition of assets. The market will pay up for real alpha and superior risk management, and is increasingly able to differentiate those from “dressed up” long only strategies.

Typically, an investor should strive to find a manager with many years of real “buy-side experience,” that is, the manager should have actually managed a reasonable amount of capital over a reasonable period of time. The exception to this rule is a new, cutting-edge manager who is implementing strategies that may not have existed three years ago. You would be surprised at how many hedge funds fail the basic “experience” test. For instance, if a manager’s only prior experience is that he was a fixed-income salesman, you could undoubtedly find someone with more relevant experience and skills. For whatever reason, a lot of hedge fund investors tend to be drawn like moths to a flame to big-name sell-side guys who come out and launch a new hedge fund. A general rule of thumb: Avoid these guys like the plague as history has shown that they tend to always fail. After all, managing capital for private investors is completely different from running market making/prop trading outfits.


pages: 302 words: 86,614

The Alpha Masters: Unlocking the Genius of the World's Top Hedge Funds by Maneet Ahuja, Myron Scholes, Mohamed El-Erian

activist fund / activist shareholder / activist investor, Asian financial crisis, asset allocation, asset-backed security, backtesting, Bernie Madoff, Bretton Woods, business process, call centre, collapse of Lehman Brothers, collateralized debt obligation, computerized trading, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, Donald Trump, en.wikipedia.org, family office, fixed income, high net worth, interest rate derivative, Isaac Newton, Long Term Capital Management, Marc Andreessen, Mark Zuckerberg, merger arbitrage, Myron Scholes, NetJets, oil shock, pattern recognition, Ponzi scheme, quantitative easing, quantitative trading / quantitative finance, Renaissance Technologies, risk-adjusted returns, risk/return, rolodex, short selling, Silicon Valley, South Sea Bubble, statistical model, Steve Jobs, systematic trading, zero-sum game

The legendary head of Goldman’s international risk arbitrage desk had left the department by the late 1980s and served as co-chairman of the firm from 1990 to 1992, when he left Goldman to join President Clinton’s economics team, first as the director of the National Economic Council, then as the Secretary of the Treasury. After Rubin moved on, Tepper continued to turn to him for advice, which didn’t sit well with Jon Corzine, the new co-head of the fixed income department. “I think that’s pretty public,” says Tepper. “People say that I basically kept going to Rubin instead of Corzine but it wasn’t for political reasons. It was just because Rubin knew what was going on with equities and Corzine was a Treasury guy that didn’t know corporates. I wasn’t disloyal to him, but I wasn’t one of his boys,” he says. “I was stupid because I was just working hard and wanted answers and to be as efficient as possible.

Sizing Up the Sweet Spot Tepper’s hope for Appaloosa is that it never gets so big that it turns into an asset gatherer rather than an investor. Instead of thinking about how to get bigger, Tepper and his team strive to decrease the amount of assets. “We don’t want to be bigger than we can invest,” he says. “The question is what size gets you—except more fees for the manager. But it doesn’t necessarily make the investor more money.” Tepper thinks that for most funds, growing over a certain amount doesn’t do anyone any good. “Fixed income funds should naturally be a little bit larger than, say, equity funds. You want to be big enough that you can see everything and small enough that you don’t kill yourself with size. So I think different sizes are right for different types of funds.” He gives an example. “Say you want to buy 5 percent of a $2 billion company, and have it be meaningful. That means it’s a $100 million position, which is a 1 percent position in a $10 billion fund.

The 1 percent position doesn’t do much for the fund and so the half percent position does half as much. So there’s an aspect to the business, in equity funds especially, that gets funky on size.” By March 2011, Appaloosa’s funds had appreciated so substantially that Tepper decided to return $600 million to investors. For the Thoroughbred Fund, however, investors had committed money for three years. The fund opened in July 2008, with a mandate to invest 70 percent of assets in fixed-income securities. Thoroughbred gained 22 percent net in 2010, after soaring 96 percent net in 2009, according to investors. The lock-up period expired at the end of 2011. Tepper reiterates that he’s in the game to make returns, not to have assets, and is looking to place some of his personal wealth with a select few other managers. But he has no desire to get out of the game. He says: “I have too much money to quit.


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Mastering the Market Cycle: Getting the Odds on Your Side by Howard Marks

activist fund / activist shareholder / activist investor, Albert Einstein, business cycle, collateralized debt obligation, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, financial innovation, fixed income, if you build it, they will come, income inequality, Isaac Newton, job automation, Long Term Capital Management, margin call, money market fund, moral hazard, new economy, profit motive, quantitative easing, race to the bottom, Richard Feynman, Richard Thaler, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, secular stagnation, short selling, South Sea Bubble, stocks for the long run, superstar cities, The Chicago School, The Great Moderation, transaction costs, VA Linux, Y2K, yield curve

In addition to short memories, psychological excesses and logical lapses, the bubble that arose in mortgage backed securities was abetted by two additional factors: Because this new bubble arose in mortgage-land—a part of the financial markets completely separate from that which had been visited by the tech and Internet bubble—the fixed income investors and financial institutions it appealed to were ones who hadn’t been affected firsthand by the other, and hadn’t learned from it. The terrible recent performance of equities had so discouraged equity investors—and interest rates brought low by the dovish Fed had so diminished the yields available on fixed income investments—that investors gave up on obtaining strong returns from stocks and bonds. That rendered them highly susceptible to the promise of a new source of return without risk: mortgage backed securities. This is a good time for a valuable aside.

Debtholders occupy a senior position relative to the equity investors, who are said to be in the “first-loss” position; this means the equity holders suffer all declines in profits, and then all losses, until the equity is wiped out, at which time any further losses fall to the debtholders. As long as there’s equity in the company, the outcome for the debtholders remains unchanged—they merely receive the interest payments they were promised. (That’s why bonds and notes are called “fixed income securities”: the outcome is fixed.) Let’s assume the capital structure of this company consists of $15,000 of debt (requiring annual interest payments of $1,500) and $15,000 of equity. That means the $1,000 decline in operating profits reduces the net income from $1,500 ($3,000 of operating profit before interest payments, minus $1,500 of interest) to $500 ($2,000 minus $1,500). In other words, a 33% decline in operating profit (from $3,000 to $2,000) causes this company’s net income to decline by 67% (from $1,500 to $500).

Our hypothetical investor wants 100 basis points to go from a “guvvie” to a “corporate.” If the consensus of investors feels the same, that’s what the spread will be. What if we depart from investment grade bonds? “I’m not going to touch a high yield bond unless I get 600 over a Treasury note of comparable maturity.” So high yield bonds are required to yield 12%, for a spread of 6% over the Treasury note, if they’re going to attract buyers. Now let’s leave fixed income altogether. Things get tougher, because you can’t look anywhere to find the prospective return on investments like stocks (that’s because, simply put, their returns are conjectural, not “fixed”). But investors have a sense for these things. “Historically S&P stocks have returned 10%, and I’ll only buy them if I think they’re going to keep doing so.” So in theory, the common stock investor determines earnings per share, earnings growth rate and dividend payout ratio and inputs them into a valuation model to arrive at the price from which S&P stocks will return 10% (although I’m not sure the process is nearly that methodical in actuality).


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Fed Up: An Insider's Take on Why the Federal Reserve Is Bad for America by Danielle Dimartino Booth

Affordable Care Act / Obamacare, asset-backed security, bank run, barriers to entry, Basel III, Bernie Sanders, break the buck, Bretton Woods, business cycle, central bank independence, collateralized debt obligation, corporate raider, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, Donald Trump, financial deregulation, financial innovation, fixed income, Flash crash, forward guidance, full employment, George Akerlof, greed is good, high net worth, housing crisis, income inequality, index fund, inflation targeting, interest rate swap, invisible hand, John Meriwether, Joseph Schumpeter, liquidity trap, London Whale, Long Term Capital Management, margin call, market bubble, Mexican peso crisis / tequila crisis, money market fund, moral hazard, Myron Scholes, natural language processing, negative equity, new economy, Northern Rock, obamacare, price stability, pushing on a string, quantitative easing, regulatory arbitrage, Robert Shiller, Robert Shiller, Ronald Reagan, selection bias, short selling, side project, Silicon Valley, The Great Moderation, The Wealth of Nations by Adam Smith, too big to fail, trickle-down economics, yield curve

At a reception given for American students by Congressman Jim Collins, Fisher’s fate collided with Texas. He had spied Collins’s pretty daughter Nancy in his classes. They married and moved to California, where Fisher earned an MBA from Stanford. Upon graduating, Fisher set his sights on Wall Street. He got a job at the investment bank of Brown Brothers Harriman & Company, where he specialized in fixed-income securities and foreign exchange markets. There he learned the first rule of banking: “Know your customer.” Despite the extraordinary odds against him, Fisher had arrived at the epicenter of the financial world, with family connections to the inner workings of America’s political establishment. But it wasn’t enough. “I’ll never make it here,” Fisher thought, as he stood on the ferry between Ellis Island and the tip of Manhattan, holding his firstborn child in his arms.

Fuld would later describe working with “gentlemen who knew what it meant when they said, ‘I am your banker.’” Fuld started in commercial paper and worked his way up. Under Glucksman’s stormy leadership, the company eventually foundered and merged with American Express. After that relationship soured, American Express spun Lehman off into a stand-alone company. When Lehman went public in 1994, Fuld steered Lehman from a fixed-income house—the bond market—into the financial innovations taking hold on Wall Street. Fuld prided himself on building a team culture inside Lehman. Many of his hires had grown up poor. Few had Ivy League degrees. He paid bonuses largely in stock, which they couldn’t sell for five years. That built loyalty and a sense of ownership—and fueled infighting and turf wars. People either loved Lehman or they left, often the victims of Fuld’s fiery temper, unceasing demands, and high self-regard.

No longer voting, Hoenig had dissented at all eight FOMC meetings in 2010, receiving no small amount of criticism. Hoenig hit back, saying that dissents at the Fed were as essential as they were at the Supreme Court. He added that the continued damage being done to more prudent players in the economy through ZIRP and QE would come back to haunt the Fed. “Importantly,” Hoenig said, “such actions as they continue are demanding the saving public and those on fixed incomes subsidize the borrowing public.” For now, Fisher remained quiet, choosing to hold his dissents for a time when change was afoot. Signs had emerged that investors were becoming desperate in response to continued zero interest rates. The search for yield took on greater intensity. On February 18, 2011, junk bond yields hit a low of 6.80 percent, dipping below the prior December 2004 record of 6.86 percent.


Triumph of the Optimists: 101 Years of Global Investment Returns by Elroy Dimson, Paul Marsh, Mike Staunton

asset allocation, banking crisis, Berlin Wall, Bretton Woods, British Empire, buy and hold, capital asset pricing model, capital controls, central bank independence, colonial rule, corporate governance, correlation coefficient, cuban missile crisis, discounted cash flows, diversification, diversified portfolio, dividend-yielding stocks, equity premium, Eugene Fama: efficient market hypothesis, European colonialism, fixed income, floating exchange rates, German hyperinflation, index fund, information asymmetry, joint-stock company, negative equity, new economy, oil shock, passive investing, purchasing power parity, random walk, risk tolerance, risk/return, selection bias, shareholder value, Sharpe ratio, stocks for the long run, survivorship bias, technology bubble, transaction costs, yield curve

To Helen, Steff, and our parents Contents Preface xi Part One: 101 years of global investment returns 1 Chapter 1 3 Introduction and overview 1.1 Need for an international perspective 3 1.2 The historical record 5 1.3 Inside the markets 7 1.4 The equity premium 1.5 Sixteen countries, one world Chapter 2 8 10 World markets: today and yesterday 11 2.1 The world’s stock markets today 11 2.2 The world’s bond markets today 14 2.3 Why stock and bond markets matter 18 2.4 The world’s markets yesterday 19 2.5 The US and UK stock markets: 1900 versus 2000 23 2.6 Industry composition: 1900 versus 2000 23 2.7 Stock market concentration 28 2.8 Summary 32 Chapter 3 Measuring long-term returns 34 3.1 Good indexes and bad 34 3.2 Index design: a case study 36 3.3 Dividends, coverage, and weightings 38 3.4 Easy-data bias in international indexes 40 3.5 Measuring inflation and fixed-income returns 43 3.6 Summary 44 Chapter 4 International capital market history 45 4.1 The US record 45 4.2 The UK record 48 4.3 Stock market returns around the world 50 4.4 Equities compared with bonds and bills 51 4.5 Investment risk and the distribution of annual returns 54 4.6 Risk, diversification, and market risk 56 4.7 Risk comparisons across asset classes and countries 59 4.8 Summary 61 vii viii Chapter 5 Inflation, interest rates, and bill returns 63 5.1 Inflation in the United States and the United Kingdom 63 5.2 Inflation around the world 65 5.3 US treasury bills and real interest rates 68 5.4 Real interest rates around the world 71 5.5 Summary 72 Chapter 6 Bond returns 74 6.1 US and UK bond returns 6.2 Bond returns around the world 79 6.3 Bond maturity premia 81 6.4 Inflation-indexed bonds and the real term premium 84 6.5 Corporate bonds and the default risk premium 87 6.6 Summary 89 Chapter 7 Exchange rates and common-currency returns 74 91 7.1 Long-run exchange rate behavior 91 7.2 The international monetary system 93 7.3 Long-run purchasing power parity 95 7.4 Deviations from purchasing power parity 96 7.5 Volatility of exchange rates 98 7.6 Common-currency returns on bonds and equities 100 7.7 Summary 103 Chapter 8 International investment 105 8.1 Local market versus currency risk 105 8.2 A twentieth century world index for equities and bonds 108 8.3 Ex post benefits from holding the world index 111 8.4 Correlations between countries 114 8.5 Prospective gains from international diversification 117 8.6 Home bias and constraints on international investment 120 8.7 Summary 123 Chapter 9 Size effects and seasonality in stock returns 124 9.1 The size effect in the United States 124 9.2 The size effect in the United Kingdom 126 9.3 The size effect around the world 129 9.4 The reversal of the size premium 131 9.5 Seasonality and size 135 9.6 Summary 138 ix Chapter 10 Value and growth in stock returns 139 10.1 Value versus growth in the United States 139 10.2 Value and growth investing in the United Kingdom 142 10.3 The international evidence 145 10.4 Summary 148 Chapter 11 Equity dividends 149 11.1 The impact of income 149 11.2 US and UK dividend growth 152 11.3 Dividend growth around the world 154 11.4 Dividend growth, GDP growth, and real equity returns 155 11.5 Dividend yields around the world and over time 157 11.6 Disappearing dividends 158 11.7 Summary 161 Chapter 12 The equity risk premium 163 12.1 US risk premia relative to bills 163 12.2 Worldwide risk premia relative to bills 166 12.3 US risk premia relative to bonds 169 12.4 Worldwide risk premia relative to bonds 171 12.5 Summary 173 Chapter 13 The prospective risk premium 176 13.1 Why the risk premium matters 177 13.2 How big should the risk premium be?

Finally, we should point out that studying the entire period since 1900—though by no means particularly easy—is easier than starting at a still earlier date. We have recently become aware of several new initiatives in this direction, but we do not know what results will be obtained from new studies of nineteenth century security prices in markets other than the United States and the United Kingdom. 3.5 Measuring inflation and fixed-income returns Most of the guiding principles listed in section 3.1 extend beyond equity indexes to the measurement of inflation and bill and bond returns. In addition, some further considerations apply. The Boskin Commission (1996) documented extensive evidence that inflation has systematically been overstated, at least in the United States, because of productivity and quality improvements. For example, the rising quality of restaurant meals in New York and London has outstripped the costs of eating out, while technology enhancements dominate the impact of changing computer prices.

Nevertheless, since few investors take a 101-year view on performance, we also need to look at risk, even in these two relatively successful markets. We turn to the question of investment risk in section 4.5. Interestingly, countries that experienced major dislocations still achieved equity market returns that were ahead of inflation. Bond and bill returns in these countries were often markedly negative, however, as these periods of economic turmoil had a more dramatic impact on fixed income than on equity investors. Figure 4-7 shows the real equity and bond return data from Table 4-1 in bar chart form, in ascending order of equity market performance from left to right. In the bond markets, the five worst performing countries (shown by the blue bars with negative returns) were among those with the lowest equity returns (on the left-hand side of the chart). These are the countries that were hit hard by hyperinflation, which we discuss further in chapter 5.


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How Money Became Dangerous by Christopher Varelas

activist fund / activist shareholder / activist investor, Airbnb, airport security, barriers to entry, basic income, bitcoin, blockchain, Bonfire of the Vanities, California gold rush, cashless society, corporate raider, crack epidemic, cryptocurrency, discounted cash flows, disintermediation, diversification, diversified portfolio, Donald Trump, dumpster diving, fiat currency, fixed income, friendly fire, full employment, Gordon Gekko, greed is good, interest rate derivative, John Meriwether, Kickstarter, Long Term Capital Management, mandatory minimum, mobile money, mortgage debt, pensions crisis, pets.com, pre–internet, profit motive, risk tolerance, Saturday Night Live, shareholder value, side project, Silicon Valley, Steve Jobs, technology bubble, The Predators' Ball, too big to fail, universal basic income, zero day

My friend and Wharton classmate Ben Giess was also coming to work at Salomon for the summer, but he was headed for the much more civilized and sophisticated investment banking department. “I don’t picture you on the trading floor,” he said. “Are you sure that’s a good idea?” Other classmates were similarly concerned. Clearly they didn’t think I had the toughness to survive in fixed income at Salomon. And I would be the first to admit that they were probably right, although I accepted the offer anyway. Sales and trading were the two main types of jobs that made up the fixed income department. The salespeople bought and sold bonds on behalf of their clients and customers, who included other investment and commercial banks, as well as large institutional investment firms such as Fidelity and PIMCO. Salespeople spent almost all of their time on the phone. The traders managed the inventory.

But as I walked onto the trading floor that June morning, I felt that I had made a fatal error. Michael Lewis would later write in Liar’s Poker, his seminal exposé of Wall Street trading, that on his first day at Salomon Brothers he felt like he was going to collect lottery winnings rather than to work. I felt like I was going to a firing squad. My classmates at The Wharton School had portrayed the fixed income department at Salomon Brothers as the wildest, most Darwinian job in the world. This investment bank, founded in 1910, was indeed the lions’ den of the Wall Street jungle, the top of the financial food chain. And somehow here I was—fresh out of Disneyland and commercial lending, an Orange County kid with a liberal arts degree. I hadn’t even known what an investment bank was just one year earlier.

My best guess as to how I made it through to the final round of interviews was that they interpreted my vague, uninformed answers as casual indifference to wanting the job. The head recruiter, the same woman who would later run our orientation, said, “People seem to like you, but we’re worried that you don’t have that salesman killer instinct.” “Okay.” I shrugged, surrendering to my fate. “But wait,” she said. Apparently the less I appeared to want it, the more desirable I became. “Let’s put you in one last interview with O’Leary, the head of fixed income sales. If you can convince him that you can sell, then you’ve got the spot.” She led me down the hall to the open door of O’Leary’s office. “Come on in,” he yelled, waving me into a seat facing him. “Listen, Mr. Varelas, despite all the glitz around working on Wall Street, we’re really just salesmen. And we need to make sure you can sell. For years now, I’ve always asked people in these interviews to sell me something.”


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MONEY Master the Game: 7 Simple Steps to Financial Freedom by Tony Robbins

3D printing, active measures, activist fund / activist shareholder / activist investor, addicted to oil, affirmative action, Affordable Care Act / Obamacare, Albert Einstein, asset allocation, backtesting, bitcoin, buy and hold, clean water, cloud computing, corporate governance, corporate raider, correlation does not imply causation, Credit Default Swap, Dean Kamen, declining real wages, diversification, diversified portfolio, Donald Trump, estate planning, fear of failure, fiat currency, financial independence, fixed income, forensic accounting, high net worth, index fund, Internet of things, invention of the wheel, Jeff Bezos, Kenneth Rogoff, lake wobegon effect, Lao Tzu, London Interbank Offered Rate, market bubble, money market fund, mortgage debt, new economy, obamacare, offshore financial centre, oil shock, optical character recognition, Own Your Own Home, passive investing, profit motive, Ralph Waldo Emerson, random walk, Ray Kurzweil, Richard Thaler, risk tolerance, riskless arbitrage, Robert Shiller, Robert Shiller, self-driving car, shareholder value, Silicon Valley, Skype, Snapchat, sovereign wealth fund, stem cell, Steve Jobs, survivorship bias, telerobotics, the rule of 72, thinkpad, transaction costs, Upton Sinclair, Vanguard fund, World Values Survey, X Prize, Yogi Berra, young professional, zero-sum game

Let me give you an example: In a 2012 Wall Street Journal article titled “How to Create a Pension (with a Few Catches),” writer Anne Tergesen highlights the benefits of putting away $100,000 today (for a male age 65) into a deferred fixed-income annuity. This man has other savings and investments, which he thinks will last him to age 85 and get him down the mountain safely. But if he lives past 85, his income insurance payments will begin, and the amounts he receives will be staggeringly large compared with how much he put in. “Currently, a 65-year-old man paying $100,000 for an immediate fixed annuity can get about $7,600 a year for life . . . But with a longevity policy [a long-term deferred fixed-income annuity—I know the language is long] that starts issuing payments at age 85, his annual payout will be $63,990, New York Life says.” Wow. At age 65, if he makes a onetime deposit of just $100,000, his payments at age 85 are close to $64,000 per year!

True, these funds aren’t insured by the FDIC, but because they are tied only to US government debt and not to any corporations or banks that might default, the only way you can lose your money is if the government fails to pay its short-term obligations. If that happens, there is no US government, and all bets are off anyway! 2. Bonds. We all know what a bond is, right? When I give you my bond, I give you my word. My promise. When I buy a bond, you give me your word—your promise—to return my money with a specific rate of interest after X period of time (the maturity date). That’s why bonds are called “fixed-income investments.” The income—or return—you’ll get from them is fixed at the time you buy them, depending on the length of time you agree to hold them. And sometimes you can use those regular interest payments (dividends) as income while the bond matures. So it’s like a simple IOU with benefits, right? But there are zillions of bonds and bond funds out there; not all but many are rated by various agencies according to their levels of risk.

In fact, some investment advisors say the only completely safe bond is one backed by the full faith and credit of the United States. And you can actually buy US bonds called Treasury inflation-protected securities, or TIPS, that rise in value to keep up with inflation through the consumer price index. Again, we’ll cover all of this in the bond briefing. And later I’ll be showing you an amazing portfolio that uses bond funds in a totally unique way. But meanwhile, let’s consider another fixed-income investment that might belong in your Security Bucket. 3. CDs. Remember them? With certificates of deposit, you’re the one loaning the money to the bank. It takes your cash for a fixed rate of interest, and then returns it—along with your earnings—after a set amount of time. Because CDs are insured by the FDIC, they’re as safe as savings accounts, and—at the time of this writing—just about as exciting.


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Warren Buffett Accounting Book: Reading Financial Statements for Value Investing (Warren Buffett's 3 Favorite Books) by Stig Brodersen, Preston Pysh

discounted cash flows, fixed income, intangible asset, market bubble, money market fund, principal–agent problem, profit maximization, risk tolerance, time value of money

From your vantage point, inflation is a constant drag or friction on your ability to make returns. Too much inflation creates uncertainty, and that is not good for lenders, companies, consumers or the exchange rate. There will be fewer investments and spending, which, as we have just learned, is not good for employment and general wealth in society. Too much inflation also means that people living on fixed incomes, such as pension benefits, experience less buying power for their money as time goes on. This brings us back to the concept of real dollars. We are interested in what we can buy for our money—not how much money we have. Or if you are in debt, like our government, you are also interested in the real value of your debt. When talking about inflation and the difference between real and nominal dollars, one should really consider what money is.

Takeaways from this chapter Let me summarize the interaction between interest rates, inflation, bonds and stocks here: Low interest rates High interest rates Low inflation Stocks Bonds High inflation Stocks Stocks Bonds are preferred in the situation where inflation is low and interest rates are high. That is partly because inflation diminishes the fixed income received from bonds, but also because a high-interest environment may yield better returns. In all other cases, stocks are likely the preferred choice. As the book progresses, I’ll provided more definitive guidance on which type of investment you should consider and why. Chapter 3 A Brief Introduction to Financial Statements For most people, financial reports are as interesting as looking at paint dry.

At the end of the day, any calculation for determining a company’s future cash flows is going to have numerous assumptions. In this book, we are going to discuss two different intrinsic value calculations so you have the flexibility to choose which approach you prefer. The first calculation is called a discount cash flow calculation. The second calculation is a variant of the discount cash flow calculation and it values stocks similarly to fixed income bonds. Although both approaches might sound a little confusing, there’s no need to worry—we’ll go step by step and provide examples on the following pages. It is important to understand that every valuation technique can be boiled down to one thing: “How much money can I expect to get in return for my initial investment?” The Discount Cash Flow (DCF) Intrinsic Value Model Let’s start with the “discount cash flow” model.


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Why Wages Rise by F. A. Harper

business cycle, collective bargaining, fixed income, full employment, means of production, wage slave

To see why, we need only review earlier historical experiences with their tragic ending of the inflation act. In speaking of the consequences of inflation at the time of the French Revolution, Andrew Dickson White said: Now began to be seen more plainly some of the many ways in which an inflation policy robs the working class . . . . the classes living on fixed incomes and small salaries felt the pressure first, as soon as the purchasing power of their fixed incomes was reduced. Soon the great class living on wages felt it even more sadly . . . . the demand for labor was diminished; laboring men were thrown out of employment . . . the price of labor . . . went down. . . . Workmen of all sorts were more and more thrown out of employment.6 So if the wage earner is to be able to enjoy further increases in real wages through a healthy and sound economic growth, inflation must be stopped.


Systematic Trading: A Unique New Method for Designing Trading and Investing Systems by Robert Carver

asset allocation, automated trading system, backtesting, barriers to entry, Black Swan, buy and hold, cognitive bias, commodity trading advisor, Credit Default Swap, diversification, diversified portfolio, easy for humans, difficult for computers, Edward Thorp, Elliott wave, fixed income, implied volatility, index fund, interest rate swap, Long Term Capital Management, margin call, merger arbitrage, Nick Leeson, paper trading, performance metric, risk tolerance, risk-adjusted returns, risk/return, Sharpe ratio, short selling, survivorship bias, systematic trading, technology bubble, transaction costs, Y Combinator, yield curve

 Systematic Trading Robert Carver worked in the City of London for over a decade. He initially traded exotic derivative products for Barclays Investment Bank and then worked as a portfolio manager for AHL – one of the world’s largest systematic hedge funds – before, during and after the global financial meltdown of 2008. He was responsible for the creation of AHL’s fundamental global macro strategy and then managed the fund’s multi-billion dollar fixed income portfolio before retiring from the industry in 2013. Robert, who has bachelors and masters degrees in Economics, now systematically trades his own portfolio of futures and equities. Every owner of a physical copy of this version of Systematic Trading can download the eBook for free direct from us at Harriman House, in a format that can be read on any eReader, tablet or smartphone. Simply head to: ebooks.harriman-house.com/systematictrading to get your free eBook now.

Leverage required depends on asset class, but is lower than for negative skew. Often requires leverage to achieve decent absolute returns in normal times; so gets killed in bad times. 40 Chapter Two. Systematic Trading Rules Positive skew Negative skew Examples: Examples: • Trend following strategies. • FX carry • Bets done by buying options, e.g. if you think the stock market will weaken then buying put options. • Fixed income relative value as practised by Long Term Capital Management (LTCM), a large hedge fund that blew up in 1998.** • John Paulson in 2006 buying cheap credit default swap insurance on securities backed by mortgages.* • Market making. • Tail protect hedge funds that try and provide cheap insurance against large market moves, as practised by Nassim Taleb amongst others. • Short option strategies, e.g. selling equity option ‘straddles’ (pairs of call and put options).

Relative value strategies which need high leverage are particularly vulnerable to crowds. Often after a long stable period of rising markets these trades get swamped by people seeking extra returns. This results in the available profits being reduced, the apparent risk falling, and required leverage increasing further. Then the music stops and their negative skew becomes horribly apparent. 45 Systematic Trading Two classic examples are the meltdown of fixed income relative value hedge fund manager Long Term Capital Management in mid-199836 and the Quant Quake – sharp losses seen over just two days by equity relative value systematic funds in August 2007. Achievable Sharpe ratios This section is relevant to all readers It’s important to have a realistic sense of what level of Sharpe ratios (SR) are achievable. As I said in the previous chapter, inflated expectations can lead to over betting (which we’ll discuss more in chapter nine, ‘Volatility Targeting’) and overtrading (see chapter twelve, ‘Speed and Size’), both of which will seriously damage your chances of trading profitably.


Risk Management in Trading by Davis Edwards

asset allocation, asset-backed security, backtesting, Black-Scholes formula, Brownian motion, business cycle, computerized trading, correlation coefficient, Credit Default Swap, discrete time, diversified portfolio, fixed income, implied volatility, intangible asset, interest rate swap, iterative process, John Meriwether, London Whale, Long Term Capital Management, margin call, Myron Scholes, Nick Leeson, p-value, paper trading, pattern recognition, random walk, risk tolerance, risk/return, selection bias, shareholder value, Sharpe ratio, short selling, statistical arbitrage, statistical model, stochastic process, systematic trading, time value of money, transaction costs, value at risk, Wiener process, zero-coupon bond

Some especially popular ETFs mirror broad market indexes like the S&P 500 or the Dow Jones Industrial Average. Real Estate Investment Trusts (REITs). REITs are investment funds which own real estate. These funds allow investors to trade real estate. BONDS (FIXED INCOME, DEBT) Debt instruments (bonds) are financial assets that are created when investors loan money to a corporation, nation, or other legal entity. These instruments allow investors to loan money to companies and receive interest payments in return. Debt instruments are often called fixed income investments because the borrower is required to make fixed payments at regular intervals that are determined when the bond is issued. The owner of the bond is the lender (creditor) and the issuer of the bond is the borrower (debtor). Bonds typically have a limited lifespan.

Each government determines which currency will be accepted as legal tender within its boundaries. Currencies are traded in the foreign exchange (FX) market. 49 Financial Markets tes st Ra Intere Bond Price s Interest Ra tes Bond Falling interest rates cause prices of already issued bonds to rise FIGURE 2.4 s Price Rising interest rates cause prices of already issued bonds to fall Bond Prices and Interest Rates KEY CONCEPT: TYPES OF DEBT SECURITIES The terms fixed income securities, bonds, and debt investments are all largely synonymous. These assets give the debt holder (the lender) a creditor position in the borrower. These instruments often have specific terms associated with them: Debenture. A debenture is an unsecured corporate bond. It is backed by the full faith and credit of the issuer. If the issuer doesn’t pay the bond, a default will be triggered that ultimately leads to bankruptcy proceedings unless a settlement is achieved.

See exchange traded funds European options, 213 exchange traded funds, 45 expected loss, 240–241 expected shortfall, 172–173 exponentially weighted volatility, 156–158 exposure at default, 240–241, 243–245 exposure, current and potential future, 260 F fair price, 26 fair value, 122, 129, 135 fair value classification, 133 fair value hierarchy, 131–134 FASB. See Financial Accounting Standards Board fill or kill orders, 19–20 303 Index Financial Accounting Standards Board, 129, 239–240 financial assets, 37 financial control, 14 financial instruments, 33–35 requirements for, 35 first derivative, 83–85 fixed income, 45–48 FOK. See fill or kill orders forced transactions, 130 foreign exchange, 48–51 forward contracts, 37, 51–54 forward curves, building, 251–252 forward prices, 21 forward testing, 100–101 front office, 12–13 functions, 62–63, 83 funds of funds, 8–9 future exposure, potential, 260 futures contracts, 37–38, 53–54 G gamma, 202, 218–225 put/call parity and, 225–226 GARCH historical volatility, 158–160 Garman-Kohlhagen, 210 generalized autoregressive conditionally heteroskedatic.


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The Oil Factor: Protect Yourself-and Profit-from the Coming Energy Crisis by Stephen Leeb, Donna Leeb

Buckminster Fuller, buy and hold, diversified portfolio, fixed income, hydrogen economy, income per capita, index fund, mortgage debt, North Sea oil, oil shale / tar sands, oil shock, peak oil, profit motive, reserve currency, rising living standards, Ronald Reagan, shareholder value, Silicon Valley, Vanguard fund, Yom Kippur War, zero-coupon bond

But when we speak of deflation in the U.S. in the early twenty-first century, we’re speaking of potential economic catastrophe. And if our oil indicator signals its onset, it’s time to rush into deflation hedges. Cash, Bonds, and Zeros Historically the only investments that perform well during the kind of economy-ravaging deflation that would occur this time around are fixed income instruments such as cash and bonds—and in particular zero coupon bonds. The most analogous period is 1929-32, and as figure 17a, “Bonds in the Depression,” shows, fixed income investments were the only shelter. More recently, deflationary fears arose when oil prices surged and acted as the catalyst that punctured the tech bubble. The sharp fall in the market threatened to cause an economic meltdown. And from mid-1999 through early 2003, bonds rose 40 percent, while zero coupon bonds scored 100 percent gains.

Why not simply put all your money into zeros? Because as we’ve noted, nothing in the market is ever a hundred percent certain, and if inflation picks up unexpectedly, your zeros will tank. Regular bonds will come down less, and they’ll still give you income. Individual bonds generally aren’t as liquid as stocks, and sometimes you can be forced to overpay for them. Thus, when it comes to investing in any fixed income instrument as a deflation hedge, we prefer the mutual fund route. One key rule is to go for quality. Don’t get tempted by high-yield bond funds, because these consist of the debt of risky companies, exactly the kind that could go broke if a depression hits. Stick to government bonds and ultra-high-quality corporate bonds. For regular bonds, our first choice is the Fidelity Investment Grade Bond Fund (1-800-544-8888), a well-managed fund that invests in high-grade bonds.


Principles of Corporate Finance by Richard A. Brealey, Stewart C. Myers, Franklin Allen

3Com Palm IPO, accounting loophole / creative accounting, Airbus A320, Asian financial crisis, asset allocation, asset-backed security, banking crisis, Bernie Madoff, big-box store, Black-Scholes formula, break the buck, Brownian motion, business cycle, buy and hold, buy low sell high, capital asset pricing model, capital controls, Carmen Reinhart, carried interest, collateralized debt obligation, compound rate of return, computerized trading, conceptual framework, corporate governance, correlation coefficient, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, cross-subsidies, discounted cash flows, disintermediation, diversified portfolio, equity premium, eurozone crisis, financial innovation, financial intermediation, fixed income, frictionless, fudge factor, German hyperinflation, implied volatility, index fund, information asymmetry, intangible asset, interest rate swap, inventory management, Iridium satellite, Kenneth Rogoff, law of one price, linear programming, Livingstone, I presume, London Interbank Offered Rate, Long Term Capital Management, loss aversion, Louis Bachelier, market bubble, market friction, money market fund, moral hazard, Myron Scholes, new economy, Nick Leeson, Northern Rock, offshore financial centre, Ponzi scheme, prediction markets, price discrimination, principal–agent problem, profit maximization, purchasing power parity, QR code, quantitative trading / quantitative finance, random walk, Real Time Gross Settlement, risk tolerance, risk/return, Robert Shiller, Robert Shiller, shareholder value, Sharpe ratio, short selling, Silicon Valley, Skype, Steve Jobs, The Nature of the Firm, the payments system, the rule of 72, time value of money, too big to fail, transaction costs, University of East Anglia, urban renewal, VA Linux, value at risk, Vanguard fund, yield curve, zero-coupon bond, zero-sum game, Zipcar

When you lend to a company, you face the risk that it will go belly-up and will not be able to repay its bonds. Defaults are rare for companies with investment-grade bond ratings, but investors worry nevertheless. Companies need to compensate investors for default risk by promising to pay higher rates of interest. ● ● ● ● ● FURTHER READING Two good general texts on fixed income markets are: F. J. Fabozzi and S. V. Mann, Handbook of Fixed Income Markets, 8th ed. (New York: McGraw-Hill, 2011). S. Sundaresan, Fixed Income Markets and Their Derivatives, 3rd ed. (San Diego, CA: Academic Press, 2009). Schaefer’s paper is a good review of duration and how it is used to hedge fixed liabilities: A. M. Schaefer, “Immunisation and Duration: A Review of Theory, Performance and Application,” in The Revolution in Corporate Finance, ed. J. M. Stern and D.

Then P&G accused Bankers Trust of misrepresenting the transactions—an embarrassing allegation, since P&G was hardly investing as a widow or orphan—and sued Bankers Trust. We take no stand on the merits of this litigation, which was eventually settled. But think of P&G’s competition when it traded in the fixed-income markets. Its competition included the trading desks of all the major investment banks, hedge funds, and fixed-income portfolio managers. P&G had no special insights or competitive advantages on the fixed-income playing field. There was no evident reason to expect positive NPV on the trades it committed to. Why was it trading at all? P&G would never invest to enter a new consumer market if it had no competitive advantage in that market. In Chapter 11 we argued that a corporation should not invest unless it can identify a competitive advantage and a source of economic rents.

Let us look at some examples. On occasion, the British and the French have been known to disagree and sometimes even to fight wars. At the end of some of these wars the British consolidated the debt they had issued during the war. The securities issued in such cases were called consols. Consols are perpetuities. These are bonds that the government is under no obligation to repay but that offer a fixed income for each year to perpetuity. The British government is still paying interest on consols issued all those years ago. The annual rate of return on a perpetuity is equal to the promised annual payment divided by the present value:4 We can obviously twist this around and find the present value of a perpetuity given the discount rate r and the cash payment C: The year is 2030. You have been fabulously successful and are now a billionaire many times over.


pages: 280 words: 79,029

Smart Money: How High-Stakes Financial Innovation Is Reshaping Our WorldÑFor the Better by Andrew Palmer

Affordable Care Act / Obamacare, algorithmic trading, Andrei Shleifer, asset-backed security, availability heuristic, bank run, banking crisis, Black-Scholes formula, bonus culture, break the buck, Bretton Woods, call centre, Carmen Reinhart, cloud computing, collapse of Lehman Brothers, collateralized debt obligation, computerized trading, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Daniel Kahneman / Amos Tversky, David Graeber, diversification, diversified portfolio, Edmond Halley, Edward Glaeser, endogenous growth, Eugene Fama: efficient market hypothesis, eurozone crisis, family office, financial deregulation, financial innovation, fixed income, Flash crash, Google Glasses, Gordon Gekko, high net worth, housing crisis, Hyman Minsky, implied volatility, income inequality, index fund, information asymmetry, Innovator's Dilemma, interest rate swap, Kenneth Rogoff, Kickstarter, late fees, London Interbank Offered Rate, Long Term Capital Management, longitudinal study, loss aversion, margin call, Mark Zuckerberg, McMansion, money market fund, mortgage debt, mortgage tax deduction, Myron Scholes, negative equity, Network effects, Northern Rock, obamacare, payday loans, peer-to-peer lending, Peter Thiel, principal–agent problem, profit maximization, quantitative trading / quantitative finance, railway mania, randomized controlled trial, Richard Feynman, Richard Thaler, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Shiller, short selling, Silicon Valley, Silicon Valley startup, Skype, South Sea Bubble, sovereign wealth fund, statistical model, Thales of Miletus, transaction costs, Tunguska event, unbanked and underbanked, underbanked, Vanguard fund, web application

Ratings are not just an important source of third-party analysis for investors, particularly smaller ones that don’t have the resources to conduct detailed assessments of every issuer’s financial health. They are also part of the skeleton of the financial system. After the 1930s (a decade now lauded for its postcrisis regulatory overhaul), US banks were required by their regulators to use credit ratings to assess the creditworthiness of the fixed-income instruments they invest in; international rules still use ratings to determine the amount of equity banks have to use to fund these assets. Investment firms use credit ratings to specify what types of fixed-income products they can invest in, and the biggest pools of capital—pension funds, sovereign-wealth funds, and the like—are often confined to “investment-grade securities,” which carry a higher rating. You can see why Andrew Lo wants to do whatever he can to win over the ratings agencies: they open the door to the largest amounts of money.

Basis risk: The risk that a hedging strategy will not work out because assets whose prices and risks are supposed to offset each other, with one rising as the other falls, do not behave as expected. Bond: An IOU issued by a company or government, which entitles the lenders to get their initial money (or principal) back as well as income in the form of an interest payment. Because bonds offer investors a fixed return, they are known as fixed-income assets. Like loans, bonds are a form of debt. Unlike loans, they are highly tradable and their ownership is very dispersed. Clearinghouse: A clearinghouse stands in between buyers and sellers in financial transactions and is designed to reduce counterparty risk. When an uncleared derivatives contract moves onto a clearinghouse, it divides into two: a contract between the buyer and the clearinghouse and a matching contract between the seller and the clearinghouse.


pages: 407 words: 114,478

The Four Pillars of Investing: Lessons for Building a Winning Portfolio by William J. Bernstein

asset allocation, Bretton Woods, British Empire, business cycle, butter production in bangladesh, buy and hold, buy low sell high, carried interest, corporate governance, cuban missile crisis, Daniel Kahneman / Amos Tversky, Dava Sobel, diversification, diversified portfolio, Edmond Halley, equity premium, estate planning, Eugene Fama: efficient market hypothesis, financial independence, financial innovation, fixed income, George Santayana, German hyperinflation, high net worth, hindsight bias, Hyman Minsky, index fund, invention of the telegraph, Isaac Newton, John Harrison: Longitude, Long Term Capital Management, loss aversion, market bubble, mental accounting, money market fund, mortgage debt, new economy, pattern recognition, Paul Samuelson, quantitative easing, railway mania, random walk, Richard Thaler, risk tolerance, risk/return, Robert Shiller, Robert Shiller, South Sea Bubble, stocks for the long run, stocks for the long term, survivorship bias, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, the rule of 72, transaction costs, Vanguard fund, yield curve, zero-sum game

Conversely, the highest returns are obtained by shouldering prudent risk when things look the bleakest, a theme we shall return to repeatedly. Bond Returns in the Twentieth Century The history of bonds in the twentieth century is unique—even the most comprehensive grasp of financial history would not have prepared the nineteenth century investor for the hurricane that buffeted the world’s fixed-income markets after 1900. In order to understand what happened, it’s necessary to briefly discuss the transition from the gold standard to the paper currency system that took place in the early 1900s. We’ve already touched on the abandonment of the gold standard after World War I. Before then, except for very brief periods, gold was money. In the U.S., there is still an abundant supply of quarter ($2.50), half ($5), full ($10), and double ($20) eagles sitting in the hands of collectors and dealers; they are still legal tender.

Mix of 50% stock/50% Treasury bill annual returns, 1901–2000. (Source: Jeremy Siegel.) Figure 4-4. Mix of 75% Stock/25% Treasury bill annual returns, 1901–2000. (Source: Jeremy Siegel.) Figure 4-5. All-stock annual returns, 1901–2000. (Source: Jeremy Siegel.) It’s important to clear up a bit of confusing terminology first. Until this point in the book, we’ve used two designations for fixed-income securities: bonds and bills, referring to long- and short-duration obligations, respectively. Bonds and bills are also different in one other respect: bonds most often yield regular interest, whereas bills do not—they are simply bought at a discount and redeemed at face value. The most common kinds of bills in everyday use are Treasury bills and commercial paper, the latter issued by corporations.

From now on, when we talk about “stocks and bonds,” what we mean by the latter is any debt security with a maturity of less than five to ten years—T-bills and notes, money market funds, CDs, and short-term corporate, government agency, and municipal bonds. For the purposes of this book, when we use the term “bonds” we are intentionally excluding long-term treasuries and corporate bonds, as these do not have an acceptable return/risk profile. I’ll admit that this is a bit confusing. A more accurate designation would be “stocks and relatively short-term fixed-income instruments,” but this wording is unwieldy. Table 4-1. 1901–2000, 100-Year Annualized Return versus 1973–1974 Bear Market Return The data in Table 4-1 and the plot in Figure 4-6 vividly portray the tradeoff between risk and return. The key point is this: the choice between stocks and bonds is not an either/or problem. Instead, the vital first step in portfolio strategy is to assess your risk tolerance.


Common Stocks and Uncommon Profits and Other Writings by Philip A. Fisher

business climate, business cycle, buy and hold, El Camino Real, estate planning, fixed income, index fund, market bubble, market fundamentalism, profit motive, RAND corporation, the market place, transaction costs

Bonds have become undesirable investments for the strictly long-term holdings of the average individual investor. The rise in interest rates that had been going on for several years gained major momentum in the fall of 1956. With high-grade bonds subsequently selling at the lowest prices in twenty-five years, many voices in the financial community were raised to advocate switching from stocks which were selling at historically high levels into such fixed-income securities. The abnormally high yield of bonds over dividend return on stocks—in relation to the ratio that normally prevails—would appear to have given strong support to the soundness of this policy. For the short term, such a policy sooner or later may prove profitable. As such, it might have great appeal for those mak-ing short- or medium-term investments—that is, for “traders” with the acuteness and sense of timing to judge when to make the necessary buying and selling moves.

In the United States this decline amounted to 29 per cent and in Canada to 35 per cent. This means that in the United States the annual rate of monetary depreciation during the period was 3.4 per cent, and in Canada it was 4.2 per cent. In contrast, the yield offered by United States Government bonds bought at the beginning of the period, which admittedly was one of rather low interest rates, was only 2.19 per cent. This means that the holder of this type of high-grade, fixed-income security actually received negative interest (or loss) of better than 1 per cent per annum if the real value of his money is considered. Suppose, however, that instead of acquiring bonds at the rather low rates that prevailed at the beginning of this period, the investor could have bought them at the rather high interest rates that prevailed ten years later. The First National City Bank of New York in the same arti-cle also supplied figures on this matter.

It seems to me that if this whole inflation mechanism is studied carefully it becomes clear that major inflationary spurts arise out of wholesale expansions of credit, which in turn result from large government deficits greatly enlarging the monetary base of the credit system. The huge deficit incurred in winning World War II laid such a base. The result was that prewar bondholders who have maintained their positions in fixed-income securities have lost over half the real value of their investments. As already explained, our laws, and more importantly our accepted beliefs of what should be done in a depression, make one of two courses seem inevitable. Either business will remain good, in which event outstanding stocks will continue to out-perform bonds, or a significant recession will occur. If this happens, bonds should temporarily out-perform the best stocks, but a train of major deficit-producing actions will then be triggered that will cause another major decline in the true purchasing power of bond-type investments.


pages: 287 words: 81,970

The Dollar Meltdown: Surviving the Coming Currency Crisis With Gold, Oil, and Other Unconventional Investments by Charles Goyette

bank run, banking crisis, Ben Bernanke: helicopter money, Berlin Wall, Bernie Madoff, Bretton Woods, British Empire, Buckminster Fuller, business cycle, buy and hold, California gold rush, currency manipulation / currency intervention, Deng Xiaoping, diversified portfolio, Elliott wave, fiat currency, fixed income, Fractional reserve banking, housing crisis, If something cannot go on forever, it will stop - Herbert Stein's Law, index fund, Lao Tzu, margin call, market bubble, McMansion, money market fund, money: store of value / unit of account / medium of exchange, mortgage debt, oil shock, peak oil, pushing on a string, reserve currency, rising living standards, road to serfdom, Ronald Reagan, Saturday Night Live, short selling, Silicon Valley, transaction costs

Maybe that confusion is to be expected from the governing classes and their lapdog press, such as the news writer who insists that the government’s bailout spending will have “no effect on Social Security and Medicare.” When his drug bill added the biggest burden to the hidden debt since the Great Society, Bush said, “This week Congress made significant progress toward improving the lives of America’s senior citizens.” Really, Mr. President? Because America’s senior citizens, and everyone else on a fixed income, will be among the hardest hit by the dollar meltdown. At least David Walker understands that failure to solve the problem of hidden debt means a depreciating dollar and a lower standard of living. “Young people in particular will end up paying double or more in taxes what the current generation pays if they don’t become more involved,” he said. Americans may be oblivious, but there are people watching our debt and the dollar very nervously.

Those financial institutions, large insurance companies, and banks have a clear moral obligation to use their considerable political clout to resist the destruction of the value of the deposits, insurance policies, and pension plans their clients have been paying for over a lifetime. But they did not do so in Germany, and they have not done so in the United States. Meanwhile, chief among the victims of inflation are those who save, such as bank depositors, those who buy bonds, and fixed income investors, retirees, and pension plan owners. In other words, all the virtues of thrift and savings that contribute to a healthy and prosperous economy are penalized. Nightmare in Zimbabwe Finally in this section a word about the recent mind-boggling runaway inflation in Zimbabwe. It is a tragic tale of bloodshed and ruin. Zimbabwe, formerly the British colony Rhodesia, was once a food exporter.

It was good for the likes of Merrill Lynch, JPMorgan, and Chase Manhattan, which saw their depressed stock prices take off, but it had a costly impact on Americans. Driving rates to 3 percent by the time he was finished, Greenspan fundamentally altered the investment outlook and risk-taking proclivities of retired people and baby boomers alike, as they sought to make up in the stock market for the certificate of deposit and fixed income returns that had disappeared. Ultimately Americans lost $6 trillion in that Greenspan stock market bubble. But while the profits of the banks from market distortions are privatized, banking system losses, as we are wit nessing, are socialized. More alarming is the role of the central bank in funding wars not popular enough to be sustained by direct taxation. This function has been on display since the Federal Reserve Act of 1913 was first passed.


pages: 285 words: 86,174

Twilight of the Elites: America After Meritocracy by Chris Hayes

affirmative action, Affordable Care Act / Obamacare, asset-backed security, barriers to entry, Berlin Wall, Bernie Madoff, carried interest, circulation of elites, Climategate, Climatic Research Unit, collapse of Lehman Brothers, collective bargaining, creative destruction, Credit Default Swap, dark matter, David Brooks, David Graeber, deindustrialization, Fall of the Berlin Wall, financial deregulation, fixed income, full employment, George Akerlof, Gunnar Myrdal, hiring and firing, income inequality, Jane Jacobs, jimmy wales, Julian Assange, Kenneth Arrow, Mark Zuckerberg, mass affluent, mass incarceration, means of production, meta analysis, meta-analysis, money market fund, moral hazard, Naomi Klein, Nate Silver, peak oil, plutocrats, Plutocrats, Ponzi scheme, Ralph Waldo Emerson, rolodex, The Spirit Level, too big to fail, University of East Anglia, Vilfredo Pareto, We are the 99%, WikiLeaks, women in the workforce

What’s more, the city was home to hundreds of thousands with disabilities, according to the 2000 U.S. census: fully 50 percent of residents over sixty-five had some kind of disability. Further compounding the problem was that the storm hit at the very end of the month, a time when those on fixed income, and Temporary Assistance for Needy Families, were at their most cash strapped. During congressional hearings devoted to untangling what went wrong during Katrina, Representative Gene Taylor pointed this out to FEMA head Michael Brown: “In all these scenarios that I’m sure you’ve thought out, did FEMA bother to realize that it is the 28th of the month, a lot of people live on fixed income, be it a Social Security check or a retirement check, they’ve already made their necessary purchase for the month. What they couldn’t envision is having to fill up their gas tank one more time, at almost 3 bucks a gallon just to get the heck out of there.”

: See Frank Bass, “Katrina’s Worst-Hit Victims Much Poorer Than Rest of America, Census Analysis Shows,” Associated Press, September 4, 2005. 22 “I’ve only got like $80 to my name”: Morning Edition, National Public Radio, September 2, 2005. 23 Among the poor nationwide, 20 percent live in households that don’t have access to a car, and among the poor in the city of New Orleans that number was 47 percent: See Alan Berube et al., “Economic Difference in Household Automobile Ownership Rates: Implications for Evacuation Policy,” pp. 7–8, http://socrates.berkeley.edu/~raphael/BerubeDeakenRaphael.pdf, accessed January 23, 2012. 24 “a lot of people live on fixed income, be it a Social Security check or a retirement check” … “It is not the role of the federal government to supply five gallons of gas”: See U.S. House of Representatives, A Failure of Initiative: Final Report of the Select Bipartisan Committee to Investigate the Preparation for and Response to Hurricane Katrina (Washington, D.C.: U.S. Government Printing Office, 2006), p. 106. http://www.gpoaccess.gov/serialset/creports/pdf/hr109-377/evac.pdf, accessed February 23, 2012. 25 “direct and compel, by any necessary and reasonable force”: This excerpt from the New Orleans Plan is quoted in A Failure of Initiative, p. 109, http://www.gpoaccess.gov/serialset/creports/pdf/hr109-377/evac.pdf, accessed February 23, 2012. 26 In his landmark study of the disaster: Eric Klinenberg, Heat Wave: A Social Autopsy of Disaster in Chicago (Chicago: University of Chicago Press, 2002). 27 “It’s hot, but let’s not blow it out of proportion”: See Sharon Cohen, “Chicago’s Heat Tragedy: ‘I’ve Never Seen So Many Dead People,’ ” Associated Press, July 22, 1995. 28 “the longest sustained combat in American history”: See Elisabeth Bumiller, “Gates Fears Wider Gap Between Country and Military,” New York Times, September 29, 2010. 29 enough money to pay the inflation-adjusted cost of Roosevelt’s New Deal twice over: The inflation-adjusted cost of the New Deal was about $500 billion.


pages: 519 words: 118,095

Your Money: The Missing Manual by J.D. Roth

Airbnb, asset allocation, bank run, buy and hold, buy low sell high, car-free, Community Supported Agriculture, delayed gratification, diversification, diversified portfolio, estate planning, Firefox, fixed income, full employment, hedonic treadmill, Home mortgage interest deduction, index card, index fund, late fees, mortgage tax deduction, Own Your Own Home, passive investing, Paul Graham, random walk, Richard Bolles, risk tolerance, Robert Shiller, Robert Shiller, speech recognition, stocks for the long run, traveling salesman, Vanguard fund, web application, Zipcar

If your risk tolerance is high, you can handle big fluctuations in your investment returns in exchange for the possibility of large gains. If your tolerance is low, on the other hand, you'd rather not deal with the ups and downs—even if that means giving up a chance at making higher returns. Some of your portfolio should be in fixed-income investments like bonds and CDs, which pay interest on a regular schedule. How much depends on your goals, needs, and risk tolerance. A common rule of thumb is that the percentage of fixed-income investments in your portfolio should be equal to your age. So, if you're 30, you should have 30% in something like a bond mutual fund. (A lot of experts dislike this guideline, but it's an easy place to start.) Most (maybe all) of the rest should be in stocks. Some of these should be stocks in American companies, and some should be in foreign companies.

Note Siegel doesn't mention it but, according to my calculations, real estate has also returned about 1% per year since 1926. Siegel goes back even further than 1926, showing that if you'd invested just one dollar in stocks in 1802, it would have been worth more than $750,000 in 2006. If you'd put that dollar in bonds instead, it would have grown to just $1,083. And if you'd put it in gold, it would be worth $1.95. (All those figures take inflation into account.) "The dominance of stocks over fixed-income securities [like bonds] is overwhelming for investors with long horizons," Siegel writes. In plain English: Over the past 200 years, stocks have outperformed every other kind of investment. But before you rush out and sink your savings in the stock market, you need to understand a few important points. Note Quick reminder: A bull market is a period of generally rising stock prices, and a bear market is a period of generally falling prices.

stocks, The Tools of Investing Escape from Cubicle Nation, Resources for Entrepreneurs estate planning, A Brief Overview of Estate Planning, Drawing up a Will, Drawing up a Will estimated taxes, Where to Get More Tax Info exchange-traded funds (ETFs), Index funds exemptions, How Income Tax Works expectations, It's Not About the Money expense notifications, Using Credit Without Getting Burned expense ratios, Mutual Funds, Keep Costs Low expenses index funds, Index funds mutual funds, Mutual Funds planning, Mapping Your Financial Future tracking, Mapping Your Financial Future Experian, Your Credit Report, How to Get Your Credit Score experiences, How Money Affects Happiness, Living a Rich Life, The Tyranny of Stuff extended warranties, Close the deal, General Insurance Tips extensions on tax returns, What To Do If You Can't Pay Uncle Sam F Fair Credit Reporting Act, Getting a Free Credit Report Fair Debt Collection Practices Act, Debtors Anonymous families, Kids and Money, Allowances FatWallet.com, Save While Shopping, Choosing a Card Federal Deposit Insurance Corporation (FDIC), Credit unions fee-only financial planners, Know Your Goals fees banks, The Right Bank for You, Keeping Your Accounts Optimized credit cards, Credit Cards, Choosing a Card mutual funds, Mutual Funds small business rates, The Pros and Cons of Entrepreneurship FICO scores, Your Credit Score Fidelity investment funds, Lifecycle funds, Mutual fund companies financial management, How Much Is Enough? financial news, Ignore the Financial News Financial Peace University, Financial Peace University financial planners, Roth IRA rules and requirements financial trolls, Coping with Mistakes and Setbacks FireCalc.com, Retirement Calculators first-time homebuyer's credit, Other moves fixed-income securities, How Much Do Stocks Actually Earn? floater policies, Homeowners Insurance foreign stock funds, Keep Costs Low, Lazy Portfolios foreign stocks, Stocks and Bonds Form 9465, What To Do If You Can't Pay Uncle Sam Form W-4, How Income Tax Works fraud, Why Use a Credit Card?, Choosing a Card, Selling a Car free checking, The Right Bank for You free credit reports, Getting a Free Credit Report Free File tax program, Hire a pro Freecycle website, Donating to Charity Freedman, Mystery shopping freedom, Friends and Family, True Wealth frequent flyer miles, Why Use a Credit Card?


pages: 327 words: 91,351

Traders at Work: How the World's Most Successful Traders Make Their Living in the Markets by Tim Bourquin, Nicholas Mango

algorithmic trading, automated trading system, backtesting, buy and hold, commodity trading advisor, Credit Default Swap, Elliott wave, fixed income, Long Term Capital Management, paper trading, pattern recognition, prediction markets, risk tolerance, Small Order Execution System, statistical arbitrage, The Wisdom of Crowds, transaction costs, zero-sum game

That’s what makes this game fun. There are boundless opportunities to come up with your own little nuances on your methods to make them just a little better. The minute you think you’ve found the key to trading, I promise you the markets will change the lock. CHAPTER 3 Serge Berger Serge Berger has been an active trader since 1998. During his career, he has been a financial analyst, dealt in fixed-income instruments at J.P. Morgan, and was a proprietary trader in equities, equity options, and futures. Exposure to a range of different asset classes has allowed Berger to identify which asset classes and strategies best fit his goal of achieving consistent profits. Over the years, Berger has created a trading methodology that divides markets into different time frames and characters, allowing him to more clearly and without emotions determine which strategies to apply in given situations.

Bourquin: Do you have a weekly goal that you set for yourself in terms of how much money you want to make? Berger: I can’t give a dollar amount, but what I can tell you is that the goal when trading the opening gap is basically to make between one and two S&P 500 E-mini futures points. If you do that, you make a very good living. Bourquin: Right. And how did you go about learning to trade the opening gap? Berger: I worked at J.P. Morgan as a fixed-income guy, and I always wanted to break loose from that and just trade, but I wanted to find something that would give me enough certainty of cash flow on a monthly or quarterly basis so I could leave, or at least get to a prop desk where I could survive. The gap trade is a very high-probability trade that allows me to do that, and that’s really why I came around it. Bourquin: Now, because the S&P may only gap a couple times a week and not every day, how often do you find that gap trade?

October 2011 was a beautiful time because of the volatility. Bourquin: Yes, low volatility always makes it tougher. Because you’re following the ECB and other central banks, are you trading currency futures at all? Berger: No. I don’t trade currency futures. And the main reason I stick with the asset classes I mentioned is because I think it gets too difficult to keep track of things. As I said earlier, I used to be a fixed-income guy and traded a lot of credit default swaps, corporate bonds, and even sovereign bonds, but it’s just too much to keep track of. Nowadays, with the advent of ETFs, if I want to get a general trade on, say, the euro or the Australian dollar, I can trade that using ETFs. Of course, I’m giving up some fees here and there, but I’m happy to just take it as a macro trade and not have to worry about the intricacies of dealing with foreign exchange and corporate bonds, because I’d then need different brokers and every­thing else.


pages: 312 words: 91,538

The Fear Index by Robert Harris

algorithmic trading, backtesting, banking crisis, dark matter, family office, Fellow of the Royal Society, fixed income, Flash crash, God and Mammon, high net worth, implied volatility, mutually assured destruction, Neil Kinnock, Renaissance Technologies, speech recognition

‘Your prime broker is AmCor, I assume, given your long relationship?’ ‘We have various prime brokers these days, not just AmCor.’ ‘More’s the pity,’ said Easterbrook, laughing. Quarry said, ‘With the greatest respect to Bill, we don’t want one single brokerage firm knowing all our strategies. At the moment we use a mix of big banks and specialist houses: three for equities, three for commodities and five for fixed income. Let’s take a look at the hardware, shall we?’ As the group moved off, Quarry pulled Hoffmann aside. ‘Am I missing something here,’ he said quietly, ‘or are those positions way out of line?’ ‘They do look a little more exposed than normal,’ agreed Hoffmann, ‘but nothing to worry about. Now I think of it, LJ mentioned that Gana wanted a meeting of the Risk Committee. I told him to talk to you about it.’

His method was to show them the independently back-tested results of Hoffmann’s algorithm and the mouth-watering projections of future returns, then break it to them that the fund was already closed: he had only fulfilled his engagement to speak in order to be polite but they didn’t need any more money, sorry. Afterwards the investors would come looking for him in the hotel bar; it worked nearly every time. Quarry had hired a guy from BNP Paribas to oversee the back office, a receptionist, a secretary, and a French fixed-income trader from AmCor who had run into some regulatory issues and needed to get out of London fast. On the technical side, Hoffmann had recruited an astrophysicist from CERN and a Polish mathematics professor to serve as quants. They had run simulations throughout the summer and had gone live in October 2002 with $107 million in assets under management. They had made a profit in the first month and had gone on doing so ever since.

Quarry said, to Hoffmann and the room, ‘We’ll need to tread very carefully. If we start liquidating positions this size too quickly, we’ll move prices.’ Hoffmann nodded. ‘That’s true, but VIXAL will help us achieve the optimums, even in override.’ He looked up at the row of digital clocks beneath the giant TV screens. ‘We’ve still got just over three hours before America closes. Imre, will you and Dieter help out with fixed income and currencies? Franco and Jon, take three or four guys each and divide up stocks and sector bets. Kolya, you do the same with the indices. Everyone else in their normal sections.’ ‘If you encounter any problems,’ said Quarry, ‘Alex and I will be here to help out. And can I just say: don’t anyone think for a second that this is a retreat. We took in an additional two billion in fresh investment today – so this shop is still growing, okay?


pages: 312 words: 93,836

Barometer of Fear: An Insider's Account of Rogue Trading and the Greatest Banking Scandal in History by Alexis Stenfors

Asian financial crisis, asset-backed security, bank run, banking crisis, Big bang: deregulation of the City of London, bonus culture, capital controls, collapse of Lehman Brothers, credit crunch, Credit Default Swap, Eugene Fama: efficient market hypothesis, eurozone crisis, financial deregulation, financial innovation, fixed income, game design, Gordon Gekko, inflation targeting, information asymmetry, interest rate derivative, interest rate swap, London Interbank Offered Rate, loss aversion, mental accounting, millennium bug, Nick Leeson, Northern Rock, oil shock, price stability, profit maximization, regulatory arbitrage, reserve currency, Rubik’s Cube, Snapchat, the market place, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, Y2K

Your friend might like the T-bill idea too, because, in theory, money could be borrowed from almost anyone. In reality, however, only large institutions are able to raise money this way. T-bills are securities that expire within a year and are issued by governments, whereas bonds refer to papers with longer maturities. Mortgage bonds are securities issued by institutions involved in mortgage lending. Considering the small size of the country, the Swedish fixed-income market (the common name for these products) was enormous. The government had borrowed a lot for an extended period of time and therefore had accumulated substantial debts. These debts could be traded in the market as securities, and this is precisely what we did. The dealing room was minuscule compared with the one I had seen in Frankfurt, containing no more than 15 or 20 seats. In fact, it looked more like a gentlemen’s club than a bank: high ceilings, expensive oak floors, chandeliers and only a discreet sign outside revealing the nature of the business conducted by Midland Montagu on Birger Jarlsgatan in Stockholm.

Legal scholars, therefore, seem to agree that if companies stand in competition with each other (such as computer manufacturers or banks), they should not collude to agree upon a predefined price component or bid–offer spread. Instead, it should be determined competitively. In 2015, the Bank of England, the UK Treasury and the FCA published a joint assessment of the financial markets following the manipulation scandals. In the Fair and Effective Markets Review, the message is clear; it states that ‘no distinction is made between wholesale and retail markets, or between FICC [fixed income, currencies and commodities] and non-FICC markets’ with regards to UK and EU competition law. The report specifically stressed that it ‘also applies to financial markets, including FX spot, which may currently fall outside of the direct scope of financial market regulation’.23 In fact, a class action has already been filed in the US in which the claimants (a long list of clients in the FX market) allege that the defendants conspired to fix bid–offer spreads for various currency pairs in the FX spot market.

Bernstein & Company, 10 Sanwa Bank, 34 Scandanavia: banking crisis, 31, 47; derivatives market, 27 secrets, 157, 170; bank employee clauses, 156, 158; value of, 157 self-confidence, hubristic sense of, 261 ‘self-detection’, 213 Service Employees International Union, USA, 163 SFO, 13 Sherman Anti-Trust Act, 220 short-term maturities, trading, 145 short-termism, 279 SIMEX (Singapore International Monetary Exchange), 127 Simmel, George, 157 skydivers, studies on, 268 Smith, Adam, 234 Smithfield market, London, 48 Snapchat, monitoring difficulty, 283 ‘snipers’, hardened traders, 66 Snow, Jon, 11; blog of, 247 SOAS (School of Oriental and African Studies), 6–7, 168 social norms, fear of retaliation, 231 Societé Générale, 194, 223 ‘sophisticated traders’, financial crisis impact on, 276 Soros, George, 32 South Korea, financial crisis, 36 Spandau Ballet, Gold, 188 ‘spoofing’, 204 Standard & Poor’s, 96 Standard Chartered, 223 Stenfors, Alexis: accusation distress, 245; childhood coins interest, 64–5; father of, 57–8; FCA five year ban, 244; FSA Final Notice, 249; guilt feelings, 69; media coverage distress, 11, 247; mismarking episode 280; press coverage, 242; silencing of, 12; threats against, 243 Stern, Andy, 163 STIBOR (Stockholm Interbank Offered Rate), 28, 76, 79; new unpredictability, 62 Stiglitz, Joseph, 225 STIRT (Short-term Interest Rate Trading) desk, 30, 40, 52, 140, 215 stock markets, benchmarks, 149 Stockholm School of Economics, 20 stop-loss order, 205–9; 258 Story, Louise, 9 Strange, Susan, ‘casino capitalism’, 171 Suez War outbreak of, 113 supply and demand, FX information, 207 swap desk, FX, 214 Swedbank, 23 Sweden, 32; banking crisis, 20; central bank, 116–17; fixed-income market, 22; FX market, 176, 178; T-bills, official rule book, 230 Swiss franc, 44; derivatives market, market makers cartel, 221 Swiss National Bank, 151 syndicated loans market, LIBOR prompting, 117–19 T-bills, 21, 230; pricing, 23 ‘take-profit orders’, 206–8 takers, market/price, 24 Telerate, LIBOR rate updating, 19 Term Auction Facility, Federal Reserve, 51 Thailand, financial crisis, 37 Thain, John, 164 Thatcher, Margaret, ‘Big Bang’, 115 TIBOR (Tokyo Interbank Offered Rate), 14, 76, 78–9, 127, 130; new unpredictability of, 62; yen, 81 TIBOR-LIBOR spread, 81, 127; ‘barometer of fear’ gauge, 36; Japanese Christmas party, 101 TIFFE (Tokyo International Financial Futures Exchange), 127 Tokyo-Mitsubishi Bank, 34 ‘Tomnext’, contracts, 145 tomorrow rate bets, LIBOR, 146 Totan brokerage, 101 trade tickets, 24; ‘Benchmark’ detail, 19; details on, 18 traders: biases, 203; bonds and FX, 27; bonuses, 56; brokers blackmailing, 90; constant observation of, 26; ‘feel’, 32; ‘profit centres’, 95; respect among, 267; risk takers, 257, 260; sloppy mistakes, 253; stereotypical perceptions of, 240 trades, 79; client prioritised, 19; speed of, 29 trading: books, 2; buzz addiction, 271; competitive, 267; computer speed, 273; principles erosion, 67; proprietary, 257; risk level, 62; risk taking, 280; rules social norms, 65; secrets, 167; ‘styles’, 47 transparency, LIBOR lack, 79 trimming process, 7, 79, 81–2 Tullett Prebon brokerage, 101, 175 Turner, Adair, 124 ‘two-way price’ making, 116 UBS bank, 92–3, 101, 153, 188, 192–3, 210, 213, 220–1, 223; bad apple narrative, 214, 236; FX scandal press release, 232; LIBOR scandal fine, 82; rogue trading scandal, 168 UK (United Kingdom): Consumer Price Index, 123; EU referendum pound fall, 171; Prudential Regulation Authority, 279; taxpayers RBS rescue, 83; Treasury, 222 University of Cologne, 17 University of Iowa, 237 USA: corporations innovative borrowing, 112; Reserve, 44–5, 50–1, 163, 174, 176, 225, 265; SEC, 180; sub-prime mortgage market, 49 US dollars, 44; demand for, 98; growing pool abroad, 112; LIBOR, 45 US dollar: LIBOR panel, 82; Middle East Europe placing, 113; trading in, 30 USSR (Union of Soviet Socialist Republics), Banque pour l’Europe du Nord, 113 Wall Street, 236, 250 Wall Street Journal 182 ‘wash trades’, 91–2, 94, 96 Weber, Axel, 213 Wheatley, Martin, 188 Whitehouse, Mark, 98 Wilson, Paul, 238–9 Winter War, USSR-Finland, 65 WM/Reuters 4pm fix, 208, 212, 277 World Trade Center Attacks, New York, 45, 264–6 yen, 33 ‘Your Amount’, trader call, 143–4 Zacher, Linda, 153 ABOUT THE AUTHOR Alexis Stenfors spent 15 years as a foreign exchange and interest rate derivatives trader at HSBC, Citi, Crédit Agricole and Merrill Lynch.


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More Money Than God: Hedge Funds and the Making of a New Elite by Sebastian Mallaby

Andrei Shleifer, Asian financial crisis, asset-backed security, automated trading system, bank run, barriers to entry, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Big bang: deregulation of the City of London, Bonfire of the Vanities, Bretton Woods, business cycle, buy and hold, capital controls, Carmen Reinhart, collapse of Lehman Brothers, collateralized debt obligation, computerized trading, corporate raider, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, currency manipulation / currency intervention, currency peg, Elliott wave, Eugene Fama: efficient market hypothesis, failed state, Fall of the Berlin Wall, financial deregulation, financial innovation, financial intermediation, fixed income, full employment, German hyperinflation, High speed trading, index fund, John Meriwether, Kenneth Rogoff, Kickstarter, Long Term Capital Management, margin call, market bubble, market clearing, market fundamentalism, merger arbitrage, money market fund, moral hazard, Myron Scholes, natural language processing, Network effects, new economy, Nikolai Kondratiev, pattern recognition, Paul Samuelson, pre–internet, quantitative hedge fund, quantitative trading / quantitative finance, random walk, Renaissance Technologies, Richard Thaler, risk-adjusted returns, risk/return, Robert Mercer, rolodex, Sharpe ratio, short selling, Silicon Valley, South Sea Bubble, sovereign wealth fund, statistical arbitrage, statistical model, survivorship bias, technology bubble, The Great Moderation, The Myth of the Rational Market, the new new thing, too big to fail, transaction costs

The Merton-Scholes hedge fund, Long-Term Capital Management, was celebrated as a stunning fulfillment of the professors’ vision. By calculating the risk of losses, Long-Term could hold the capital it needed and no more, turning minuscule price anomalies into fabulous profits. Yet as the scholars savored their glory, Long-Term reached a fateful crossroads. Back in the 1980s, Meriwether and his professors had been the upstarts on Wall Street; one decade on, nearly all investment banks had fixed-income arbitrage desks that competed with them directly.23 In the first half of 1997, LTCM’s profits had started to slow down, and the partners began to do some soul-searching. One response to shrunken opportunity was to shrink the fund, returning money to investors. But LTCM was not ready to shrink to the point of giving up. To keep the money machine going, Meriwether and his team began to venture into equities.

Unfortunately, its strategies turned out to overlap with the sorts of arbitrage practiced by LTCM and its imitators. The result was that D. E. Shaw got hurt in the bond-market turbulence that accompanied Long-Term Capital’s collapse in 1998—“It could have been the end of the game for Shaw at that point,” one of the firm’s traders said later. The company sold part of its trading book, taking a loss that wiped out that year’s gains in all its other strategies combined. Having learned how highly leveraged fixed-income strategies could get hit in a liquidity crunch, Shaw abandoned bond arbitrage for a few years, though by 2002 it had tiptoed back into it. WHILE SHAW WAS BUILDING HIS MACHINE, ANOTHER effort was under way in a surprising corner of the industry. Paul Tudor Jones, rock-and-roll trader and Robin Hood founder, was investing the fruits of his winnings in a computer-trading project. The early phases of this effort were in keeping with Jones’s exuberant youth.

This was the sort of risky bet that made sense to a deep-pocketed, fee-hungry parent. It would have been less likely to fly with a real hedge fund. Ralph Cioffi himself was not the sort of figure who could have launched his own hedge fund easily. As a salesman, he had virtually no experience in controlling portfolio risk—indeed, some Bear executives argued that he should not be allowed to do so. Paul Friedman, the COO of Bear’s fixed-income desk, said afterward, “There were a fair number of skeptics internally who couldn’t figure out how this guy—who was bright but had never managed money—was now going to be running money. He knew nothing about risk management, had never written a ticket in his life that wasn’t someone else’s money.”15 Likewise, Cioffi was short on managerial ability: In a brief stint as a supervisor, he had performed disappointingly.


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Adaptive Markets: Financial Evolution at the Speed of Thought by Andrew W. Lo

"Robert Solow", Albert Einstein, Alfred Russel Wallace, algorithmic trading, Andrei Shleifer, Arthur Eddington, Asian financial crisis, asset allocation, asset-backed security, backtesting, bank run, barriers to entry, Berlin Wall, Bernie Madoff, bitcoin, Bonfire of the Vanities, bonus culture, break the buck, Brownian motion, business cycle, business process, butterfly effect, buy and hold, capital asset pricing model, Captain Sullenberger Hudson, Carmen Reinhart, collapse of Lehman Brothers, collateralized debt obligation, commoditize, computerized trading, corporate governance, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, Daniel Kahneman / Amos Tversky, delayed gratification, Diane Coyle, diversification, diversified portfolio, double helix, easy for humans, difficult for computers, Ernest Rutherford, Eugene Fama: efficient market hypothesis, experimental economics, experimental subject, Fall of the Berlin Wall, financial deregulation, financial innovation, financial intermediation, fixed income, Flash crash, Fractional reserve banking, framing effect, Gordon Gekko, greed is good, Hans Rosling, Henri Poincaré, high net worth, housing crisis, incomplete markets, index fund, interest rate derivative, invention of the telegraph, Isaac Newton, James Watt: steam engine, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Meriwether, Joseph Schumpeter, Kenneth Rogoff, London Interbank Offered Rate, Long Term Capital Management, longitudinal study, loss aversion, Louis Pasteur, mandelbrot fractal, margin call, Mark Zuckerberg, market fundamentalism, martingale, merger arbitrage, meta analysis, meta-analysis, Milgram experiment, money market fund, moral hazard, Myron Scholes, Nick Leeson, old-boy network, out of africa, p-value, paper trading, passive investing, Paul Lévy, Paul Samuelson, Ponzi scheme, predatory finance, prediction markets, price discovery process, profit maximization, profit motive, quantitative hedge fund, quantitative trading / quantitative finance, RAND corporation, random walk, randomized controlled trial, Renaissance Technologies, Richard Feynman, Richard Feynman: Challenger O-ring, risk tolerance, Robert Shiller, Robert Shiller, Sam Peltzman, Shai Danziger, short selling, sovereign wealth fund, Stanford marshmallow experiment, Stanford prison experiment, statistical arbitrage, Steven Pinker, stochastic process, stocks for the long run, survivorship bias, Thales and the olive presses, The Great Moderation, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Thomas Malthus, Thorstein Veblen, Tobin tax, too big to fail, transaction costs, Triangle Shirtwaist Factory, ultimatum game, Upton Sinclair, US Airways Flight 1549, Walter Mischel, Watson beat the top human players on Jeopardy!, WikiLeaks, Yogi Berra, zero-sum game

Until 2006, Sweden also had unusually complete financial reporting requirements for individuals. This combination allowed three financial economists—Amir Barnea, Henrik Cronqvist, and Stephan Siegel—to analyze the relative differences in financial portfolios between pairs of identical twins, who share the same DNA, and pairs of fraternal twins, who are only as closely related as any pair of biological siblings.32 They looked at the proportion of assets held in cash, in bonds and fixed income securities, in equities directly, in equities held in funds, and in other financial assets such as rights, convertibles, and warrants. And what Barnea, Cronqvist, and Siegel discovered was remarkable. By comparing the performance of pairs of fraternal and identical twins, they found that a third of the observed investment behavior in the Swedish twin portfolios could be attributed to genetics: 29 percent of stock market participation, 32 percent of the share of equities, and 38 percent of portfolio volatility.

Few regulators wanted an extinction event that could turn the global financial system into a wasteland of barnacles on the beach. The Fed helped to form a consortium of LTCM’s major creditors to recapitalize the firm just in time to avoid a hard landing.34 LTCM wasn’t the only hedge fund to be hit by this financial meteor strike, but it was certainly the biggest. The aftermath of the Russian bond default disrupted a very specific group of hedge funds and trading desks, those using a fi xed-income arbitrage strategy. Fixed-income arbitrage funds experienced an 18 percent attrition rate in 1998, more than double the baseline rate until the financial crisis of 2008. From an evolutionary perspective, only the exceptional size of LTCM made its collapse stand out. Interestingly enough, the events of 1998 failed to make a noticeable impact in the attrition rate of other categories of hedge funds. Instead of a mass financial extinction, 1998 was highly selective, affecting one particular niche in the financial ecology.

Second, few commercial banks were involved in statarb in 1998, but because of the relatively low-risk/high-return performance of Shaw, Renaissance, and other statarb managers, and the growing need for higher yielding assets in the declining-yield environment of the early 2000s, these banks started to take an interest. By 2007, all of the major banks were running statarb portfolios of their own, which meant that sufficiently severe losses to their subprime mortgage holdings could force them to liquidate their statarb portfolios to raise cash for margin calls. This link between fixed-income credit markets and statarb strategies didn’t exist in 1998, as our simulations showed, but clearly existed in 2007. Finally, an additional channel linking the mortgage crisis and statarb was the growing popularity of funds of hedge funds (funds that invest in a broadly diversified portfolio of other hedge funds) and multistrategy funds (funds that employ many different types of strategies). Although such funds existed in 1998, they were fewer in number and much smaller in size.


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The Little Book of Common Sense Investing: The Only Way to Guarantee Your Fair Share of Stock Market Returns by John C. Bogle

asset allocation, backtesting, buy and hold, creative destruction, diversification, diversified portfolio, financial intermediation, fixed income, index fund, invention of the wheel, Isaac Newton, new economy, passive investing, Paul Samuelson, random walk, risk tolerance, risk-adjusted returns, Sharpe ratio, stocks for the long run, survivorship bias, transaction costs, Upton Sinclair, Vanguard fund, William of Occam, yield management, zero-sum game

But the relentless rules of humble arithmetic with which I’ve regaled you also apply—arguably even more forcefully—to bond funds. Perhaps it’s obvious why this is so. While a seemingly infinite number of factors influence the stock market and each individual stock that is traded there, a single factor dominates the returns earned by investors in the bond market: the prevailing level of interest rates. Managers of fixed-income funds can’t do much, if anything, to influence rates. If they don’t like the rates established in the marketplace, neither calling the Treasury Department or the Federal Reserve, nor otherwise trying to change the supply/demand equation, is likely to bear fruit. Why would an intelligent investor hold bonds? Over the long term, history tells us that stocks have generally provided higher returns than bonds.

Indeed, many of the earlier chapters in this book that were focused on stock funds could just as easily be the titles of a series of bond fund chapters—especially, “Focus on the Lowest-Cost Funds,” “Selecting Long-Term Winners,” and “Profit from the Majesty of Simplicity and Parsimony.” These rules are universal. Don’t Take My Word for It The power of bond indexing is growing. Peter Fisher, former head of the fixed-income group at giant global money manager BlackRock, has observed: “We’re moving to the second phase of the index revolution. The world is a frightening, uncertain place, and investors want to make their [bond] portfolios much simpler so they can sleep at night.” * * * While not a lot has been written about the remarkable (and remarkably obvious) value of index funds that invest in bonds, the convictions expressed in this chapter have been strongly reinforced by Walter R.


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Bad Samaritans: The Myth of Free Trade and the Secret History of Capitalism by Ha-Joon Chang

affirmative action, Albert Einstein, Big bang: deregulation of the City of London, bilateral investment treaty, borderless world, Bretton Woods, British Empire, Brownian motion, business cycle, call centre, capital controls, central bank independence, colonial rule, Corn Laws, corporate governance, David Ricardo: comparative advantage, Deng Xiaoping, Doha Development Round, en.wikipedia.org, falling living standards, Fellow of the Royal Society, financial deregulation, fixed income, Francis Fukuyama: the end of history, income inequality, income per capita, industrial robot, Isaac Newton, joint-stock company, Joseph Schumpeter, Kenneth Rogoff, Kickstarter, land reform, liberal world order, liberation theology, low skilled workers, market bubble, market fundamentalism, Martin Wolf, means of production, mega-rich, moral hazard, Nelson Mandela, offshore financial centre, oil shock, price stability, principal–agent problem, Ronald Reagan, South Sea Bubble, structural adjustment programs, The Wealth of Nations by Adam Smith, trade liberalization, transfer pricing, urban sprawl, World Values Survey

But, if moderate inflation is not harmful, why are neo-liberals so obsessed with it? Neo-liberals would argue that all inflation – moderate or not – is still objectionable, because it disproportionately hurts people on fixed incomes – notably wage earners and pensioners, who are the most vulnerable sections of the population. Paul Volcker, the chairman of the US Federal Reserve Board (the US central bank) under Ronald Reagan (1979–87), argued: ‘Inflation is thought of as a cruel, and maybe the cruellest, tax because it hits in a many-sectored way, in an unplanned way, and it hits the people on a fixed income hardest’.16 But this is only half the story. Lower inflation may mean that what the workers have already earned is better protected, but the policies that are needed to generate this outcome may reduce what they can earn in the future.

Prudence, it seems, has become the supreme virtue in a finance minister. Emphasis on fiscal prudence has been a central theme in the neo-liberal macroeconomics promoted by the Bad Samaritans. They argue that government should not live beyond its means and must always balance its budget. Deficit spending, they argue, only leads to inflation and undermines economic stability, which, in turn, reduces growth and diminishes the living standards of people on fixed income. Once again, who can argue against prudence? But, as in the case of inflation, the real question is what exactly it means to be prudent. For one thing, being prudent does not mean that the government has to balance its books every year, as is preached to developing countries by the Bad Samaritans. The government budget may have to be balanced, but this needs to be achieved over a business cycle, rather than every year.


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Secrets of Sand Hill Road: Venture Capital and How to Get It by Scott Kupor

activist fund / activist shareholder / activist investor, Airbnb, Amazon Web Services, asset allocation, barriers to entry, Ben Horowitz, carried interest, cloud computing, corporate governance, cryptocurrency, discounted cash flows, diversification, diversified portfolio, estate planning, family office, fixed income, high net worth, index fund, information asymmetry, Lean Startup, low cost airline, Lyft, Marc Andreessen, Myron Scholes, Network effects, Paul Graham, pets.com, price stability, ride hailing / ride sharing, rolodex, Sand Hill Road, shareholder value, Silicon Valley, software as a service, sovereign wealth fund, Startup school, Travis Kalanick, uber lyft, VA Linux, Y Combinator, zero-sum game

As with its domestic equity allocation, Yale’s foreign equity allocation trails the average university endowment by about 6 percentage points. Over the last twenty years, Yale’s foreign equity portfolio has returned about 14 percent annually. Hedge funds—Yale calls its hedge fund strategy “absolute return,” meaning that it is investing in this asset class largely to generate high long-term returns by exploiting market inefficiencies with relatively low correlation to broader equity market and fixed income returns. Yale’s allocation of 22 percent to absolute return strategies is generally in line with other university endowments and has returned 9 percent annually over the last twenty years (with the expected low correlation to equities and bonds). Buyout funds—Yale has a 15 percent allocation to buyout funds; recall that these are private equity funds that typically buy controlling ownership stakes in existing businesses and seek to increase their value over time by improving their financial operations.

Real estate—Yale has a 12.5 percent allocation to real estate investments, well in excess of the 4 percent average at other university endowments. Over the last twenty years, Yale’s real estate portfolio has returned about 11 percent annually. The smallest portion of Yale’s endowment is targeted to deflation hedging assets—7.2 percent, well below the 12.7 percent allocation of the average university endowment: Fixed income—Yale has a 4.9 percent allocation to bonds, which are intended to protect against unexpected deflation and to provide near-term cash flow. Over the last twenty years, Yale’s bond portfolio has returned about 5 percent annually. Cash—Yale has about a 2 percent allocation to cash. A couple of big-picture things stand out when looking at the Yale endowment portfolio. Yale has a heavy concentration in illiquid assets—Yale targets to have about 50 percent of its endowment in illiquid assets (essentially funds where the money is tied up for longer periods of time).

., 11 fiduciary duties and Bloodhound case, 236–239 to debt holders, 246 in difficult financing scenarios, 232, 236, 237 dual fiduciaries, 201–202, 212 duty of candor, 215 duty of care, 211–212, 215, 217 duty of confidentiality, 212–215 duty of loyalty, 212, 215, 218 and winding down the company, 246 financial crisis of 2008, 59 financial forecasts, 150–151 fixed income, 63 foreign equities, 62 foundations, 55, 57 founders adaptability of, 49 and board of directors, 97–98, 171–172 and capitalization tables, 190–191 and common stock, 93 and company vs. product-first companies, 44–45 departure of cofounders, 94–95, 96–100 egomania in, 47–48 and evaluation of early-stage companies, 43, 44, 49 founder-market fit, 45–47, 131–133 and information asymmetry, 5, 140, 275 and intellectual property, 101–103 leadership abilities of, 47–48 and product development, 49 and stock restrictions in term sheets, 181 and storytelling skills, 134 and taxation, 71 and vesting, 95–97, 99–101, 183, 186–187, 205–206 409A opinions, 205 fraud, accusations of, 218 Freenome, 128 full ratchet, 166 funds of funds, 56 general partners (GPs) and board seats, 179, 214–215 and carried interest, 74–77 and choosing a corporate structure, 93–94 and clawbacks, 80–81 co-investments of, 86–87 compensation of, 73–77 as dual fiduciaries, 202 and equity partners agreement, 88–89 and exit of VC after IPO, 267 and indemnification, 89–90 investments as domain of, 85–86 and LP–GP relationship, 70–71, 85–88 and management fee, 72–74 and managing conflicts, 214–215 obligations of, 87 and state of fund, 84 suspension of, 87–88 and vesting, 89 See also limited partnership agreement Glass-Steagall Act, 54 going to market, 135–138 good corporate governance, 206–207 Google, 10, 25, 41 Gornall, Will, 3 go-shop provisions, 239, 255 governance terms in term sheets, 196–198 Graham, Paul, 20 green shoe, 265 growth assets, 57–58, 61–63 HA Angel Fund (Horowitz Andreessen Angel Fund), 19 The Hard Thing about Hard Things (Horowitz), 18 hedge funds, 57–58, 62 Hewlett-Packard, 18–19 Hindawi, David, 46 Hindawi, Orion, 46 Horowitz, Ben and Andreessen Horowitz, 21–22, 270 angel investing, 19 aspirin/vitamin analogy of, 50 on founders’ leadership capabilities, 47 The Hard Thing about Hard Things, 18 interview with, 12–13, 14 “hurdle rates,” 83 illiquid assets, 64 incentive stock options (ISOs), 104–105, 185 indemnification, 89–90, 183, 253 inflation, 56–57, 61 inflation hedges, 58, 63 information asymmetry, 5, 140, 275 information rights, 282 initial coin offerings (ICOs), 274 initial public offerings (IPOs), 257–268 and alternative forms of financing, 108–109 and conversion to common shares, 160–161 costs involved in, 107 declining number of, 106–109, 160–161, 249 and dot.com boom/bust, 9–10, 15 effects of efficiency rules on, 107–108 and emerging growth companies (EGCs), 261–263 and exit of VC, 2, 266–267 and the green shoe, 265 and initial filing range, 17 and liquidity, 258–260, 265 and lockup agreements, 265–266 mutual funds’ impact on, 108 percentage of venture backed, 3 and pressure on public companies, 109 pricing, 263–265 process of, 260–268 and prospectus, 261, 263 and reasons to go public, 257–260 and road shows, 263 and secondary offering of shares, 267–268 time frame for, 10 Instacart, 45 Instagram, 45, 130 institutional investors, 29–30, 40–41 insurance companies, 56, 57 intellectual property, 101–103 invention and assignment agreements, 101 investment banks, 260–261 investors’ role in venture capital, 29.


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