asset allocation

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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

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asset allocation, backtesting, Bernie Madoff, Black Swan, 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, Richard Feynman: Challenger O-ring, risk tolerance, risk-adjusted returns, risk/return, selection bias, Sharpe ratio, short selling, statistical model, 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

Issues in Alpha and Beta Determination Problems in Alpha and Beta Determination Multi-Factor Return Estimation: An Example Tracking Alternatives in Alpha Determination Notes xi xix 1 3 4 6 11 14 15 17 20 22 24 26 28 30 33 34 37 39 39 46 48 50 54 56 v vi CONTENTS CHAPTER 4 Asset Classes: What They Are and Where to Put Them Overview and Limitations of the Existing Asset Allocation Process Asset Allocation in Traditional and Alternative Investments: A Road Map Historical Return and Risk Attributes and Strategy Allocation Traditional Stock/Bond Allocation versus Multi-Asset Allocation Risk and Return Comparisons Under Differing Historical Time Periods Extreme Market Sensitivity Market Segment or Market Sensitivity: Does It Matter? How New Is New? Notes CHAPTER 5 Strategic, Tactical, and Dynamic Asset Allocation Asset Allocation Optimization Models Strategic Asset Allocation Tactical Asset Allocation Dynamic Asset Allocation Notes CHAPTER 6 Core and Satellite Investment: Market/Manager Based Alternatives Determining the Appropriate Benchmarks and Groupings Sample Allocations Core Allocation Satellite Investment Algorithmic and Discretionary Aspects of Core/Satellite Exposure Replication Based Indices Peer Group Creation—Style Purity Notes 58 59 61 66 70 71 74 82 84 88 91 92 99 101 107 109 110 111 117 119 120 120 122 126 132 Contents CHAPTER 7 Sources of Risk and Return in Alternative Investments Asset Class Performance Hedge Funds Managed Futures (Commodity Trading Advisors) Private Equity Real Estate Commodities Notes CHAPTER 8 Return and Risk Differences among Similar Asset Class Benchmarks Making Sense Out of Traditional Stock and Bond Indices Private Equity Real Estate Alternative REIT Investments Indices Commodity Investment Hedge Funds Investable Manager Based Hedge Fund Indices CTA Investment Index versus Fund Investment: A Hedge Fund Example Notes CHAPTER 9 Risk Budgeting and Asset Allocation Process of Risk Management: Multi-Factor Approach Process of Risk Management: Volatility Target Risk Decomposition of Portfolio Risk Management Using Futures Risk Management Using Options Covered Call Long Collar Notes CHAPTER 10 Myths of Asset Allocation Investor Attitudes, Not Economic Information, Drive Asset Values Diversification Across Domestic or International Equity Securities Is Sufficient vii 134 135 139 143 148 153 160 166 167 168 170 173 179 179 185 185 189 189 194 195 195 200 202 203 206 206 208 210 212 213 214 viii CONTENTS Historical Security and Index Performance Provides a Simple Means to Forecast Future Excess Risk-Adjusted Returns Recent Manager Fund Return Performance Provides the Best Forecast of Future Return Superior Managers or Superior Investment Ideas Do Not Exist Performance Analytics Provide a Complete Means to Determine Better Performing Managers Traditional Assets Reflect “Actual Values” Better Than Alternative Investments Stock and Bond Investment Means Investors Have No Derivatives Exposure Stock and Bond Investment Removes Investor Concerns as to Leverage Given the Efficiency of the Stock and Bond Markets, Managers Provide No Useful Service Investors Can Rely on Academics and Investment Professionals to Provide Current Investment Models and Theories Alternative Assets Are Riskier Than Equity and Fixed Income Securities Alternative Assets Such as Hedge Funds Are Absolute Return Vehicles Alternative Investments Such as Hedge Funds Are Unique in Their Investment Strategies Hedge Funds Are Black Box Trading Systems Unintelligible to Investors Hedge Funds Are Traders, Not Investment Managers Alternative Investment Strategies Are So Unique That They Cannot Be Replicated It Makes Little Difference Which Traditional or Alternative Indices Are Used in an Asset Allocation Model Modern Portfolio Theory Is Too Simplistic to Deal with Private Equity, Real Estate, and Hedge Funds Notes CHAPTER 11 The Importance of Discretion in Asset Allocation Decisions The Why and Wherefore of Asset Allocation Models Value of Manager Discretion 215 215 216 216 217 217 218 218 218 219 220 221 222 222 223 223 223 225 226 226 230 Contents Manager Evaluation and Review: The Due Diligence Process Madoff: Due Diligence Gone Wrong or Never Conducted Notes CHAPTER 12 Asset Allocation: Where Is It Headed?

This chapter provides a brief history of how major advances in financial theory and investment practice affected investors’ approach to asset allocation and how asset allocation has had to evolve to meet changes in economic, regulatory, and technological environments. However, given the range of current and past efforts to diagnose, describe, and prescribe the process of asset allocation, it seems relatively futile to provide any reasonable summary of how we got here, much less what “here” is. Before reviewing how we have arrived at current approaches to asset allocation, a brief review of what asset allocation is seems appropriate. Simply put, the ability to estimate what the future returns and risks of a range of investors’ acceptable investments are and to choose a course of action based upon those alternatives is at the heart of asset allocation. As a result, much of asset allocation is centered on the quantitative tools or approaches used to estimate the probabilities of what may happen (risk) and the alternative approaches to managing that risk (risk management).

Today, investment in a larger range of investable assets is being addressed through more active asset construction. The increase in potential investment opportunities increases the potential benefit of strategic asset allocation opportunities as well as tactical and dynamic approaches to asset allocation. Chapter 5 addresses those issues. The term asset allocation means different things to different people in different contexts. For our purposes we have divided asset allocation decisions into three often-used categories: O ■ ■ Strategic asset allocation can be characterized as a long-term asset allocation decision. The objective is to determine the long-term normal asset mix that will represent the desirable balance of risk and return. In developing the strategic asset allocation, the investor’s return objectives, risk tolerance, and other investment constraints have to be taken into account.


pages: 337 words: 89,075

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

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accounting loophole / creative accounting, airline deregulation, Andrei Shleifer, asset allocation, Bretton Woods, 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, 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, survivorship bias, the market place, transaction costs, Y2K, yield curve, zero-sum game

See also asset classes; cyclical asset allocation (CAA); strategic asset allocation (SAA) elasticity effect on, 213-217 fixed-income asset allocation, 25-26, 37-38, 119 location-based asset allocation, 24-25, 34-37, 125-126 long-run asset allocation, 40-43, 118, 127, 274-275, 285n periodic table of asset returns, 46 portable-alpha strategy, 256-257, 260-264, 269-270 retirement planning and, 3-4 size-based asset allocation, 23-24, 31-32, 123 style-based asset allocation, 18, 22-23, 26-30, 121 tactical asset allocation (TAA), xx, 18, 60, 101, 254 asset classes. See also asset allocation annual returns, 19 mean-reversion hypothesis, 4, 18 Monte Carlo simulations, 4-6 performance of, 16-18 periodic table of asset returns, 6-11 selecting, 18-21 single asset buy-and-hold, 12-13 types of, 5 asset-allocation consultants, 3 B basis points, 30 benchmarks. See also passive management cyclical asset allocation (CAA) compared to, 141-142 strategic asset allocation (SAA) as, 104 historical allocations, 104-108, 113-115 lifecycle allocations, 115-116 market allocations, 108-115, 266-269 ERISA, 284n beta, 19, 21, 113 active versus passive management, 252-255 elasticity and, 211-212 swing assets, 290n in value-timing strategy, 243-250 Bretton Woods standard, 89 broad market.

See also returndelivery vehicles correlation of markets, 186 country effects. See location effect coupon rate, 128 cyclical asset allocation (CAA), xx, 18 asset class selection, 18-21 basis of, 100 equity/fixed-income cycles, 53-54 fixed-income asset allocation and, 37-39, 119 fixed-income cycles, 48-52 forecasts and, 100-101, 127-129 hedge funds and, 230-239 investor convictions and, 129-142, 275-281 location cycles, 57-58 location effect, 202-204 location-based asset allocation and, 34-37, 125-126 long-run asset allocation and, 40-43, 118, 127, 274-275 portable-alpha strategy versus, 261 size cycles, 54-55 size-based asset allocation and, 31-32, 123 strategic asset allocation (SAA) versus, 59-65, 254 style cycles, 55-57 style-based asset allocation and, 26-30, 121 tax-rate changes and. See tax-rate changes as value-timing strategy, 243-250 versatility of, 144 financial-management firm for highnet-worth case study, 145-146, 149 global financial management plan case study, 149-152 hedge funds case study, 157-161 lifecycle funds case study, 152-157 cyclical stocks, 5 D debt financing, tax-rate changes and, 73-76 demand shifts, 218-224 310 diversification, PPP (purchasing power parity) and, 185-187 dividends, 72, 82-84.

Asset Allocation Weight Region International 0% Style Asset Type Equities Size Value Large 100% 20% Growth 60% 0% Asset Allocation 0% 12% 0% 100% Domestic 100% Small 80% 40% 48% 40% Fixed Income Figure 6.1 Asset allocation produced by the historical returns of asset classes using the Sharpe ratio to select the optimal mix: 1978–2004. Chapter 6 To Start, a Benchmark 107 Asset Allocation Weight Region International 36.7% 18.7% Style Value Asset Type Size Equities Large 45.7% 51.2% 47% Growth 56.3% Asset Allocation 7.0% 8.6% 63.3% Domestic 100% Small 53% 17.2% Fixed Income 48.8% 48.8% Figure 6.2 Asset allocation based on the percentage of time allocated by the Sharpe ratio to each asset class: 1975–2004. Market-Based Asset Allocation Weights Another major objection I have to traditional asset allocation is its partialequilibrium nature. SAA assumes the individual investor has no market power. In the economic parlance, the individual investor is the quintessential atomistic investor—he is a price-taker and has no influence on prices.

All About Asset Allocation, Second Edition by Richard Ferri

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activist fund / activist shareholder / activist investor, asset allocation, asset-backed security, barriers to entry, Bernie Madoff, 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, survivorship bias, too big to fail, transaction costs, Vanguard fund, yield curve

How Behavior Affects Asset Allocation Decisions 289 The answers to these questions will help you develop a general asset allocation based on your tolerance for risk. However, more work will be required to develop an appropriate portfolio for your needs. NOTE 1 Olivia S. Mitchell and Stephen P. Utkus, Lessons from Behavioral Finance for Retirement Plan Design, Wharton School and Vanguard Center for Retirement Research, November 24, 2003. This page intentionally left blank CHAPTER 14 When to Change Your Asset Allocation KEY CONCEPTS ● ● ● ● Asset allocation decisions are typically not permanent. Life changes lead to asset allocation changes. Too much risk in a portfolio should be managed downward. Estate planning needs eventually set asset allocation. Asset allocation changes can take two forms.

The above reasons are three of the most common triggers for an asset allocation change, although there are many other reasons. For example, starting a new business may prompt people to become more conservative in their asset allocation because they are now taking business risk in other ways as well as needing extra liquidity. A divorce could change both spouses’ asset allocation as each party looks to his or her financial future as a single person rather than as a couple. A serious medical issue may change longterm goals, and this may affect asset allocation. Finally, the death of a spouse may also affect asset allocation decisions because one person has lower liabilities than two. Whatever the reason for an asset allocation review, it should be done with as much care and diligence as your initial allocation. Any change to an asset allocation should be long term and with the intent to match long-term liabilities and savings goals.

CONTENTS Foreword by William Bernstein v Acknowledgments vii Introduction viii PART ONE: ASSET ALLOCATION BASICS Chapter 1 Planning for Investment Success 3 Chapter 2 Understanding Investment Risk 25 Chapter 3 Asset Allocation Explained 41 Chapter 4 Multi-Asset-Class Investing 65 PART TWO: ASSET-CLASS SELECTION Chapter 5 A Framework for Investment Selection 87 Chapter 6 U.S. Equity Investments 101 Chapter 7 International Equity Investments 127 iii CONTENTS iv Chapter 8 Fixed-Income Investments 147 Chapter 9 Real Estate Investments 171 Chapter 10 Alternative Investments 189 PART THREE: MANAGING YOUR PORTFOLIO Chapter 11 Realistic Market Expectations 219 Chapter 12 Building Your Portfolio 243 Chapter 13 How Behavior Affects Asset Allocation Decisions Chapter 14 When to Change Your Asset Allocation 291 Chapter 15 Fees Matter in Asset Allocation Planning 301 Appendix A: Research Web Sites 317 Appendix B: Recommended Reading Glossary Index 321 331 319 271 FOREWORD In the fall of 1929, Alfred Cowles III had an ordinary, if rather large, problem.

The Intelligent Asset Allocator: How to Build Your Portfolio to Maximize Returns and Minimize Risk by William J. Bernstein

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asset allocation, backtesting, capital asset pricing model, commoditize, computer age, correlation coefficient, diversification, diversified portfolio, Eugene Fama: efficient market hypothesis, fixed income, index arbitrage, index fund, intangible asset, Long Term Capital Management, p-value, passive investing, prediction markets, random walk, Richard Thaler, risk tolerance, risk-adjusted returns, risk/return, South Sea Bubble, survivorship bias, the rule of 72, the scientific method, time value of money, transaction costs, Vanguard fund, Yogi Berra, zero-coupon bond

International Publishing, 1993. 197 This page intentionally left blank Index Active management, 95–99 Alpha, 89–90, 98 American Association of Individual Investors, 177 American Depositary Receipts (ADRs), 78 Annualized return, 2–3, 5 Asset Allocation (Gibson), 176 Asset-allocation funds, 162–164 Asset-allocation strategy, 26, 143–174 asset-allocation funds in, 162–164 bonds in, 151–152 determining allocation, 143–145, 153–154 dynamic, 137–139, 163–164 executing plan for, 154–161 investment resources for, 175–180 key points for, 173–174 retirement accounts and, 153–154 stock indexing in, 145–151 taxes and, 145 Treasury ladders in, 152 (See also Asset classes; Diversification; Optimal asset allocation) Asset classes: 1926–1998, 9–18, 42 1970–1998, 19–21 in asset allocation process, 76–83 correlation coefficients among, 183–186 law of diminishing returns and, 76 standard deviation of annual returns, 6 Asset variance, 109 Autocorrelation, 106–108 Average return, 2–3 Backtesting, 72 Barra indexes, 99, 126 Baruch, Bernard, 52 Behavioral finance, 139–142 defined, 139 overconfidence and, 139–140 recency and, 47–48, 52, 53, 58–59, 140–141 risk aversion myopia and, 141–142 Benchmarking: alpha in, 89–90, 98 with S&P 500, 60, 78, 79, 86, 88–90, 145 Benzarti, Shlomo, 131 Bid-ask spread, 91, 92, 93, 96 Binomial distribution function, 2, 7 Bogle, John, 175–176 Bond funds, 151–152 Bonds: in asset allocation strategy, 151–152 common stock versus, 24 historical returns of, 23, 24 standard deviation of annual returns, 6 Book value (P/B ratio): data on ranges of, 114 in new era of investing, 124 in value investing, 112–113, 120 variation in returns and, 116–117 Brinson, Gary, 176 Buffett, Warren, 118 Calibration, 140 Capital gains capture, 102, 108 Center for Research in Security Prices, 76 Charles Schwab, 100 Clayman, Michelle, 118 Coin-toss option, 1–5, 29–36, 169 Commissions, 90–91, 92, 96, 152 Common Sense on Mutual Funds (Bogle), 175–176 199 200 Index Common stocks: 1926–1998, 4, 13–16, 17, 42–45 discounted dividend method and, 23–24, 26, 127–132 growth, 97, 112, 117 historical returns on, 23–25 large-company, (See Large-company stocks) long bonds versus, 24 risks and returns of, 1–5 small-company (See Small-company stocks) standard deviation of annual returns, 5–8, 63, 65, 96 Company size: variation in returns and, 116–117 (See also Large-company stocks; Small-company stocks) Complex portfolios, 41–62 defined, 41 efficient frontier, 55–59, 64 foreign assets in, 46–53 professional versus small investors, 59–61 rebalancing, 59 return and risk plot, 41–45 risk dilution, 45–46 small versus big stocks in, 53–55, 75 Compound interest, 17 Constant allocation, 58 Contrarian approach, 59, 104 Contrarian Market Strategy (Dreman), 104 Conventionality, in asset allocation process, 78–79 Cooley, Philip L., 169 Corner portfolios, 65–71 Correlation, 36–40 among asset classes, 183–186 autocorrelation, 106–108 calculating, 39 defined, 37 foreign investments and, 46–53, 72–73 imperfect, 37 Correlation (Cont.): negative, 31, 37 overstating of diversification benefits, 71-74 of small stocks and large stocks, 53–55 zero, 31 Cost of capital, 132 Critical-line technique, 65 Currency risk, 132–137 Dimensional Fund Advisors (DFA), 20, 148, 149, 150, 164 analysis of fund performance 1970–1998, 86 bond funds, 152 global large company index, 74–75 moderate balanced strategy, 82 small-cap index, 54–55, 98–99, 100 Discount rate (DR), 127–130 Discounted dividend method: Glassman-Hassett model and, 127–132 nature of, 23–24, 26 Diversification, 19, 21, 144 benefits of, 33–36, 41–45, 71–74 impact on risk and return, 31–36, 63 international, 46–53, 72–75 overstatement of benefits of, 71–74 (See also Optimal asset allocation) Dividend yield: data on ranges of, 114, 115 market declines and, 166–167 in new era of investing, 124 in value investing, 113–115 Dividends: Dow dividend strategy, 116 growth of, 80 reinvesting, 115 REITs and, 145 Dodd, David, 176 Dollar cost averaging (DCA), 154–155, 159 Dow 36,000 (Glassman and Hassett), 127–132 Dow dividend strategy, 116 Dow Jones Industrial Average, 24–25, 26, 80 Index Dreman, David, 104, 117 Dunn’s law, 99–100 Duration risk, 165–167 Dynamic asset allocation, 137–139 defined, 137 market valuation and, 163–164 overbalancing in, 138 EAFE Index, 38, 39, 46–53, 100, 126 Earnings yield, 119 Econometrics of Financial Markets, The (Campbell, Lo, and MacKinlay), 107–108 Edleson, Michael, 155–159, 176 Efficient frontier, 55–59, 64 Efficient market hypothesis, 104–105, 118–119, 120 Efficient Solutions, 65–71, 181–182 Ellis, Charles, 94 Emerging markets, 49–50, 100, 147–148 European bonds, 152 European stocks, 19, 20, 25, 156 efficient frontier and, 55–59 hedging with, 133 mutual funds, 147 Excess risk, 12–13 Exchange traded funds (ETFs), 149, 151 Expense ratio (ER), 90, 91, 92, 96, 146 Expert opinion, 74 Fama, Eugene, 98, 109, 116–117, 120–124, 148 Financial calculators, 5, 168 Fisher, Kenneth, 109 Fixed asset allocation, 109 Forbes, Malcolm, 104 Foreign assets: correlation and, 47, 72–73 EAFE Index, 38, 39, 46–53, 100, 126 hedging with, 132–137 Foreign tax credit, 161 Forward premium, 135 Forward rates, 135–136 Fraud, investment, 4 French, Kenneth, 98, 116–117, 120–124, 126, 148 201 Fund of funds, 161 Future optimal portfolio composition, 64 Gibson, Roger, 176 Glassman, James, 127–132 Global Investing (Ibbotson and Brinson), 176 Goetzmann, William, 49–50 Gold stocks (See Precious metals equity) Graham, Benjamin, 24, 93, 106, 112, 117, 118, 119–120, 125, 176–177 Graham, John, 104 Grant, James, 178 Great Depression, 14, 19, 112, 166 Growth investing: defined, 112, 118 efficient market theory and, 118–119 value investing versus, 117, 118–120 Growth stocks, 97, 112, 117 Harvey, Campbell, 104 Hassett, Kevin, 127–132 Haugen, Robert A., 119, 176 Hedging, 132–137 cost of, 135–136 defined, 132 extent of, 136–137 Historical optimal allocation, 64 Hubbard, Carl M., 169 Hypothetical optimal allocation, 64 Ibbotson, Roger, 176 Ibbotson Associates, 9–10, 23, 41–42, 44, 93, 178 Imperfect correlation, 37 In sample, 87 In Search of Excellence (Peters), 118 Indexing, 94–103 advantages over active management, 95–99 defined, 95 international, 100 mutual funds in, 145–151, 174 202 Index Indexing (Cont.): of small-company stocks, 101, 102, 148–149 theoretical advantage of, 95–96 Inflation, and real return, 80, 168 Institutional investors: evaluation of, 123–124 market-impact costs and, 86–90, 91–92, 96 pension funds, 103 persistence of investment performance, 90 small investors versus, 59–61 (See also Benchmarking; Mutual funds) Intelligent Investor, The (Graham), 106, 176–177 International diversification: case against, 72 correlation and, 46–53, 72–73 with small stocks, 74–75 sovereign risk and, 72 Inverse correlation, 31, 37 Investment climate, 124–127 Investment Company Institute, 103 Investment fraud, 4 Investment newsletters, 104–105 January effect, 92–94 Japanese bonds, 152 Japanese stocks, 19, 20, 25, 38, 39, 40, 48, 55, 56, 57, 59, 160 Jensen, Michael, 86 Jorion, Phillipe, 49–50 Keynes, John Maynard, 18 Lakonishok, Josef, 120 Large-company stocks, 13 indexing advantage with, 96, 97–98 small-company stocks versus, 53–55, 75 Law of diminishing returns, 76 Lehman Long Bond Index, 162 Local return, 133 Long Term Capital Management, 7 Mackay, Charles, 178 Malkiel, Burton, 101–102, 109, 175 Market capitalization, 13 Market efficiency, 85–110 expenses of funds and, 90–92, 96, 146 indexing and, 94–101 investment newsletters and, 104–105 January effect, 92–94 market-impact costs and, 88–90, 91–92, 96 and persistence of investment performance, 85–88 random walk and, 101, 106–108 rebalancing and, 108–109 survivorship bias and, 101–102 taxes and, 102–103 Market-impact costs: extent of, 91, 92, 96 illustration of, 88–90 Market multiple (See P/E ratio) Market risk premium, 121, 122 Market timing, 104–105, 160 Market valuation, 111–115, 163–164, 174 Markowitz, Harry, 64–65, 71, 177–178 Maximum-return portfolios, 69 Mean reversion, 70, 107, 109 Mean-variance analysis, 44–45, 64–71, 181–182 Mean-variance optimizers (MVOs), 64–71, 181–182 Memoirs of Extraordinary Popular Delusions and the Madness of Crowds (Mackay), 178 Miller, Paul, 115 Minimum-variance portfolios, 65–69 Momentum investing, 101, 108, 109, 123 Money managers (See Institutional investors; Mutual funds) Money market, standard deviation of annual returns, 6 Morgan-Stanley Capital Indexes, 19–20, 133, 149 Index Morningstar: long-term returns, 21 Principia database, 61, 96–97, 101–102, 120, 163–164, 177 standard deviation and, 6, 19 MSCI World Index, 162 Multiple (See P/E ratio) Multiple-asset portfolios, 29–40 coin toss and, 36 correlation in, 36–40 diversification and, 31–36 simple portfolios versus, 31–36 Multiple change, 24 Mutual funds: asset-allocation, 162–164 bond, 151–152 exchange traded (ETFs), 149–151 expenses of, 90–92, 96, 146 hedging, 135 indexing with, 145–151, 174 standard deviation and, 6 supermarkets, 148 turnover of, 130–131 Vanguard Group, 97–100, 146–148, 149, 150, 152, 156, 161–163 MVOPlus, 65–71, 181–182 National Association of Real Estate Investment Trusts (NAREIT), 21 Negative correlation, 31, 37 New era of investing: components of, 124–127 Glassman-Hassett model and, 127–132 New Finance: the Case Against Efficient Markets (Haugen), 119, 176 Newsletters, investment, 104–105 Nonsystematic risk, 12–13 Normal distribution, 7 Oakmark Fund, 88–90 Optimal asset allocation, 63–83 asset-allocation funds in, 162–164 asset classes in, 76–78 calculation of, 64–71 conventionality and, 78–79 203 Optimal asset allocation (Cont.): correlation coefficients, 71–74 international diversification with small stocks, 74–75 risk tolerance and, 79–80, 143 three-step approach to, 75–83 Out of sample, 87 Overbalancing, 138 Overconfidence, 139–140 P/B ratio (See Book value) P/E ratio: data on ranges of, 113, 114 earnings yield as reverse of, 119 in new era of investing, 124 in value investing, 112, 119–120 Pacific Rim stocks, 19, 20, 21, 25, 55–59, 147, 156 Pension funds, 103 (See also Institutional investors) Perfectly reasonable price (PRP), 127–128 Performance measurement: alpha in, 89–90, 98 three-factor model in, 123–124 (See also Benchmarking) Perold, Andre, 141 Persistence of performance, 85–88 Peters, Tom, 118 Piscataqua Research, 103 Policy allocation, 59 Portfolio insurance, 141 Portfolio Selection (Markowitz), 177–178 Precious metals stocks, 19–20, 21, 48, 55, 57, 59 Price, Michael, 162 Professional investors (See Institutional investors) Prudent man test, 60 Random Walk Down Wall Street, A (Malkiel), 101–102, 175 Random walk theory, 106–108, 119 positive autocorrelation and, 106–108 204 Index Random walk theory (Cont.): random walk defined, 106 rebalancing and, 109 Raskob, John J., 16–17 Real estate investment trusts (REITs), 38, 40, 100, 145 defined, 19 index fund, 148 returns on, 19, 21, 25 Real return, 26, 80, 168, 170 Rebalancing: frequency of, 108–109 importance of, 32–33, 35–36, 59, 63, 174 and mean-variance optimizer (MVO), 65 overbalancing in, 138 random walk theory and, 109 rebalancing bonus, 74, 159–160 of tax-sheltered accounts, 159–160 of taxable accounts, 160–161 Recency effects, 47–48, 52, 53, 58–59, 140–141 Regression analysis, 89–90 Reinvestment risk, 23 Representativeness, 118 Research expenses, 92, 95 Residual return, 98 Retirement, 165–172 asset allocation for, 153–154 duration risk and, 165–167 shortfall risk and, 167–172 (See also Tax-sheltered accounts) Return: annualized, 2–3, 5 average, 2–3 coin toss and, 1–5 company size and, 116–117 correlation between risk and, 21 dividend discount method, 23–24, 26, 127–132 efficient frontier and, 55–58 expected investment, 26 historical, problems with, 21–27 Return (Cont.): impact of diversification on, 31–36, 63 market, 168 real, 26, 80, 168, 170 return and risk plot, 31–36, 41–45 risk and high, 18 uncorrelated, 29–31 variation in, 116–117 Risk: common stock, 1–5 correlation between return and, 21 currency, 132–137 duration, 165–167 efficient frontier and, 55–58 excess, 12–13 high returns and, 18 impact of diversification on, 31–36, 63 nonsystematic, 12–13 reinvestment, 23 return and risk plot, 31–36, 41–45 shortfall, 167–172 sovereign, 72 systematic, 13 (See also Standard deviation) Risk aversion myopia, 141–142 Risk dilution, 45–46 Risk-free investments, 10, 15, 152 Risk-free rate, 121 Risk time horizon, 130, 131, 143–144, 167 Risk tolerance, 79–80, 143 Roth IRA, 172 Rukeyser, Lou, 174 Rule of 72, 27 Sanborn, Robert, 88–90 Securities Act of 1933, 92–93 Security Analysis (Graham and Dodd), 93, 118, 125, 176 Selling forward, 132–133 Semivariance, 7 Sharpe, William, 141 Shortfall risk, 167–172 Siegel, Jeremy, 19, 136 Index Simple portfolios, 31–36 Sinquefield, Rex, 148 Small-cap premium, 53, 121, 122 Small-company stocks, 13–16, 25 correlation with large-company stocks, 53–55 efficient frontier and, 55–59 indexing, 101, 102, 148–149 international diversification with, 74–75 January effect and, 92–94 large-company stocks versus, 53–55, 75 “lottery ticket” premium and, 127 tracking error of, 75 Small investors, institutional investors versus, 59–61 Solnik, Bruno, 72 Sovereign risk, 72 S&P 500, 13, 38, 39, 55 as benchmark, 60, 78, 79, 80, 86, 88–89, 145 efficient frontier, 56–57 Spiders (SPDRS), 149 Spot rate, 135 Spread, 91, 92, 93, 96 Standard deviation, 5–8 defined, 6, 63 limitations of, 7 of manager returns, 96 in mean-variance analysis, 65 Standard error (SE), 87 Standard normal cumulative distribution function, 7 Stocks, Bonds, Bills, and Inflation (Ibbotson Associates), 9–10, 41–42, 178 Stocks for the Long Run (Siegel), 19, 136 Strategic asset allocation, 58–59 Survivorship bias, 101–102 Systematic risk, 13 t distribution function, 87 Tax-sheltered accounts: asset allocation for, 153–154 rebalancing, 108–109, 159–160 (See also Retirement accounts) 205 Taxable accounts: asset allocation for, 153–154 rebalancing, 160–161 Taxes: in asset allocation strategy, 145 capital gains capture, 102, 108 foreign tax credits, 161 market efficiency and, 102–103 Technological change: historical, impact of, 125 in new era of investing, 125 Templeton, John, 164 Thaler, Richard, 131, 142 Three-factor model (Fama and French), 120–124 Time horizon, 130, 131, 143–144, 167 Tracking error: defined, 75 determining tolerance for, 83, 145 of small-company stocks, 75 of various equity mixes, 79 Treasury bills: 1926–1998, 10–11 returns on, 25–26 as risk-free investments, 10, 15, 152 Treasury bonds: 1926–1998, 11–13, 42–45 ladders, 152 Treasury Inflation Protected Security (TIPS), 80, 131–132, 172 Treasury notes, 11 Turnover, 95, 102, 130–131, 145 Tweedy, Browne, 148–149, 162, 176 Utility functions, 7 Value averaging, 155–159 Value Averaging (Edleson), 176 Value index funds, 145 Value investing, 77, 111–124 defined, 118 growth investing versus, 117, 118–120 measures used in, 112–114 studies on, 115–118 three-factor model of, 120–124 Value premium, 121–123 206 Index VanEck Gold Fund, 21 Vanguard Group, 97–100, 146–148, 149, 150, 152, 156, 161–163 Variance, 7, 108–109 mean-variance analysis, 44–45, 64–71, 181–182 minimum-variance portfolios, 65–69 Variance drag, 69 Walz, Daniel T., 169 Websites, 178–180 Wilkinson, David, 56, 57, 181–182 Williams, John Burr, 127 Wilshire Associates, 120, 147, 162 World Equity Benchmark Securities (WEBS), 149–151 z values, 87 Zero correlation, 31 About the Author William Bernstein, Ph.D, M.D., is a practicing neurologist in Oregon.

Whether you like it or not, you are a money manager. Asset allocation accounts for most of the difference in performance among money managers. Arriving at an effective asset allocation is both critically important and not that hard to do. Long-term success in individual security selection and market timing is difficult to impossible; fortunately, they are nearly irrelevant. The failure of market timing and active security selection will be discussed in Chapter 6. 4. Since the future cannot be predicted, it is impossible to specify in advance what the best asset allocation will be. Rather, our job is to find an allocation that will do reasonably well under a wide range of circumstances. 5. Sticking by your target asset allocation through thick and thin is much more important than picking the right asset allocation. 63 64 The Intelligent Asset Allocator The Calculation of Optimal Allocations First of all, let’s be clear about what we mean when we say “optimal allocations.”

I recommend the new Vanguard Tax-Managed International Fund for this purpose.) 162 The Intelligent Asset Allocator The Everything Fund Is it possible to find a single fund which will relieve you of all of the trouble of asset allocation? Sure—the mutual fund industry is nothing if not responsive to every whim of the investing public. There are many funds which will provide you with what they consider to be the “optimal” asset allocation; these are called, naturally, asset-allocation funds. There are a few problems with these funds. First, they have not been around for very long, so it is hard to evaluate them. Second, what little track record they do have is not particularly impressive. The average 10-year annualized return (for April 1988–March 1999) of Morningstar’s asset-allocation and global funds was 10.79%, compared with 17.70% for the broadly based Wilshire 5000, and 9.08% for the Lehman Long Bond Index.


pages: 345 words: 87,745

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

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asset allocation, backtesting, Bernie Madoff, 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

Table 6.1 Four Portfolio Choices for Investors Passive Funds (index funds and benchmark based ETFs) Active Funds (mutual funds and actively managed ETFs) Maintain a Fixed Passive Asset Allocation Passive funds Passive allocation Active funds Passive allocation Employ a Tactical Active Asset Allocation Passive funds Active allocation Active funds Active allocation Starting with asset allocation first; there are two schools of thought. The first follows a fixed passive allocation also known as strategic asset allocation. In this approach, investments are allocated to a fixed allocation of asset classes that’s based on long-term needs and are held at that allocation through regular rebalancing. In contrast, a tactical asset allocation is all about actively shifting mutual fund weights based on near-term predictions of asset class returns. A tactical asset allocation decision may last from a few days to a few years.

The idea is to place part of the portfolio in a strategic asset allocation using index funds and ETFs, and then play with the remaining part of the portfolio using tactical asset allocation. I call these combined strategies core and pay more because that best describes the outcome. The cost of the explore side is more expensive than the core side, and there’s no reason to believe that the active management results will be any better simply because there is less of it. Investors will likely earn market returns for their passive positions in index funds and below market returns in that portion using tactical asset allocation. Investment returns for a passive strategic asset allocation are much more likely to earn superior returns than those earned from tactical asset allocation strategies. The nuances of strategic and tactical asset allocation strategy go beyond the scope of this book.

Investors should be aware of which asset classes, styles, and sectors are better placed in tax-advantaged accounts such as a tax-sheltered retirement account and those that are suitable for taxable accounts. Asset allocation is the cornerstone of a prudent investment plan and is the single most important decision that an investor will make in regard to a portfolio. Many issues need to be considered when developing an investment plan. Getting this part of the investment policy right is of paramount importance. Investors would do well to study this subject intently and nail down an appropriate asset allocation that fits their needs. Step 3: Select an Asset Allocation The backbone of an investment plan is its asset allocation. At the 50,000-foot level, asset allocation is all about developing overall return goals while controlling risk. At the 5,000-foot level, it is about the expected risk and return of major asset classes and the correlations between those risks and returns.

The Smartest Investment Book You'll Ever Read: The Simple, Stress-Free Way to Reach Your Investment Goals by Daniel R. Solin

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asset allocation, corporate governance, diversification, diversified portfolio, index fund, market fundamentalism, money market fund, Myron Scholes, passive investing, prediction markets, random walk, risk tolerance, risk-adjusted returns, risk/return, transaction costs, Vanguard fund, zero-sum game

J (Cadsby), 181 Q uestionnaire, ruse t Allocation. Su Asset Allocation Questionnaire Quinn, Jane Bryant, 93, 94 radio programs. Se, financial media Random walk Down WaD Street, A {Malkicl),90, 148, 153, 181 RAS (Risk Assessment Score), 175-78 Su also Asset Allocation Questionnaire ratings, Morningstar, 55-57, 158-59 192 Index ratio, management expense (MER),62--63, 135 rebalancing portfolios, 120, 132-33 regulations for SC(;urities industry, 82, 141-42, 164, 165, 170 Rekenthalcr, John, 55 religious organizations, as Smart Investors, 106 retirement planning. Su Asset Allocation Questionnaire retirement plans (RRPs and RRSPs) ETFs in, 139-40, 169-70 Risk and Return Summary, 179-80 Risk Assessment Score (RAS), 17S--78 Ser also Asset Allocation Questionnaire risk management about risk management, 41 about asset allocation and, 40-41,70-72, 121 - 22 abo ut investment portfolios, 122-23 buying on margin and, 77-78 ETI;s and, 86-87 international stocks and, 130-31,169 prospectus information on risks,60 research on, 162--63 risk return comparison (chart), 14, 74-76 standard deviation to measure risk, 67--68, 85, 126, 138 Su also asset allocation; investment portfolios Rodgers, Kelly, 161 Ross, Ron, 132, 136 RRPs and RRSPs, ETFs in, 139-40, 169-70 Samuelson, Paul A., 107, 163 Sanford, Jeff, 164 Savings-Age Score (SAS), 172-73 Srr also Asset Allocation Questionnaire Scholes, Myron S., 107 Schwab, C harles, 59 Securities Exchange Commission (U.S .), 163 securities industry about the industry, 8-9 analyst fraud in, 39-40, ISS broker/client trust issues, 37, 39-41 , 98-101 ,138, J55, 168 disadvantages of use of, 149-50, ISS-56 house funds, 77-78, 163 myths of, 3-4, 9, 12, 146 qualifications of advisors, 42-43,52 regulation of, 82, 14 1-42, 164, 165, 170 U.S. brokers in Canada's industry, 119, 152 U.S.lCanada similarities, xi-xii Su also financial media; market timing {predicting the future}; stock and fu nd picking Sharpe, William E, 13, 34, 107 Siegel, Jeremy, 73 Simon, Scott, 148 Singer, Brian D., 121 , 162 Index 193 Sinha, Rajceva, 51, 107, 151 Sinquefield, Rex, 145 "sizzle" in H yperactive Trwestor, 32-33 small cap stocks, 113-14 Smart Investo rs about being a Smart Investor, 18-19,75, 144 benefits of being a, 6, 25, 137 books for, 93,152, 181-82 fa mous investors as, 107-9, 168 institutional investors as, 89, 105-7.114,168 percent of all trades, 138 See auo ETFs (exchange traded fu nds); Four-Step Process for Smart Investors; index funds; ris k management Smarr Investor Advisors contact with investors, 133 DFAas, 11 2-14, 168 for large investors, 89 for risk management, 40 when to use an advisor, 114 Smith Barney ho use funds, 77, 163 S&P 500 ETF, 15 S&P 500 Index, 15, 24 S&P Composite Index (U.S.), 29,45, 151 S&prrSX Composite Index about S&PfT'SX composite index, 23-24 standard deviation and risk, 68 use as a benchmark, 46, 83, 135 speculative investing and gambling, 30-3 1,153-54 Spinet, Eliot L, 39, 40 standard deviation, as risk measurement, 67-68, 85, 126, 138 State Street Global Advisors, 106 Stiglin, Joseph E., 163 stocks about stocks, 13-14, 84-87 as asset class, 13,40, 71, 121 buying on margin, 77-78 earnings per share (EPS), 14 international stocks, 19, 130-3 1, 169 prospectus for a stock, 60 risk and, 122-23 risk return comparison (chart), 14, 74-76 small-cap stocks, 113-14 standard deviation to measure price fluctuations, 67-68, 85,126, l38 U.S. stocks. 19, 119, 160 value stocks, 84-87, 114 Su also investment portfolios stock and fu nd picking about stock picking, 6-7, 17, 51-54 COSts and fees, 27-28, 35 decline of, 109-10, 149-50, 168 as desire for order, 31 myths of,}-4, 37, 70,146 research on, 53, 168 stock brokers.

Ellis, Invmmmt Policy Another imponant factor in proper investing-after taking account of COS t S and understanding risk-is asset allocation. Asset allocation refers to the percentage of an investment portfolio held in each of the major asset classes-stocks, bonds and cash. Many academic studies have shown that the vast majo rity of a portfolio's variabili ty in retu rns is accou nted for by asset allocation. Very little is accounted fo r by either market timing or by picking the "right" security within an asset class. Therefore, it is curious that aU the hype you hear from hyperactive bro kers and advisors relates to market timing and stock picking. When is the last time your hyperactive broker called yo u for the sole purpose of discuss ing your asset allocation? Too Many Stocks, Too Few Bonds 71 Most Hyperactive Investors have portfolios that are underweighted in bonds and overweighted in stocks.

There are also all kinds of questionnaires available on the internet that you can fill out to determine your optimal asset allocation. Many of them suffer from oversimplification and arc really not of much value. I have prepared a questionnaire fo r those of you who want to validate your asset allocation decision (see Appendix A). While it is not uncomplicated, you should be able to fill it out in about 15 minutes. 124 The Rea! \\'ay Smart Im'estors Beat 95%of the ~Pros" A much easier and even quicker way to use this questionnaire is to go to the website for this book, www.smartest investmentbook.com-a site that is programmed to be interactive, with all of the calculations performed automatically. While no questionnaire, including the one in this book, should be the only source you rely on to determine your asset allocation, my questionnaire is a reliable guide to helping you find the right asset allocation for you.


pages: 363 words: 28,546

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

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asset allocation, Bretton Woods, 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, superstar cities, survivorship bias, transaction costs, Vanguard fund

P1: a/b c13 P2: c/d QC: e/f JWBT412-Marston 272 T1: g December 10, 2010 15:51 Printer: Courier Westford PORTFOLIO DESIGN allocation to alternatives with those of other university endowments as reported by NACUBO, the National Association of College and University Business Officers. Each year NACUBO conducts a survey of its members to determine the asset allocations that their endowments are following. NACUBO reports two sets of figures, those that equally weight all colleges and universities and a dollar-weighted average. The massive size of the endowments of the richest institutions ensures that the dollar-weighted average is heavily influenced by the asset allocation decisions of the biggest endowments. In 2008, the top 10 institutions had 36 percent of the endowment monies of the 791 institutions in the survey. The dollar-weighted average, therefore, better reflects the asset allocations of Yale’s peers. Figure 13.6 shows the asset allocations over more than three decades. In 1985 when Swensen took over the Yale Endowment, Yale’s allocation to alternatives was still only 11.7 percent compared with NACUBO’s equalweighted average of 4.9 percent.14 By 2008, NACUBO’s average allocation to alternatives had increased to 23.5 percent while Yale’s had risen to 74.6 percent.

P1: a/b c14 P2: c/d QC: e/f JWBT412-Marston T1: g December 8, 2010 18:59 302 Printer: Courier Westford P1: a/b c15 P2: c/d QC: e/f JWBT412-Marston T1: g December 20, 2010 17:6 Printer: Courier Westford CHAPTER 15 Investing and Spending in Retirement fter a foundation chooses its asset allocation, it should be able to leave that allocation unchanged for the indefinite future. As the last chapter showed, a foundation can set up a spending plan and choose a long-run strategic asset allocation to support it. Unless there is major distress in the markets, the foundation should be able to carry out its plans without making changes to its allocation. It will hire and fire managers, but the overall investment plan should remain unchanged. Some foundations, of course, will pursue tactical asset allocation in an attempt to take advantage of shortterm opportunities to overweight or underweight specific asset classes. But usually the tactical asset shifts are relative to a strategic (i.e., long-run) asset allocation that remains unchanged. Individual investors are different.

Figure 15.3 shows that experts can disagree about the specific asset allocation. But it’s clear that for all such programs, the asset allocation is governed by savings and spending decisions for retirement. This is the reason why a book on asset allocation has a separate chapter for retirement. QC: e/f JWBT412-Marston T1: g December 20, 2010 17:6 Printer: Courier Westford 305 Investing and Spending in Retirement Bonds Stocks 100% Porolio Allocaon c15 P2: c/d 75% 50% 25% 0% 45 40 35 30 25 20 15 10 5 R R+5 Years unl Rerement FIGURE 15.2 Vanguard’s Target Portfolio Allocations Determined by Years until Retirement Source: www.vanguard.com. 100% 75% Porolio Allocaons P1: a/b Foreign Stocks U.S. Stocks Cash & Bonds 50% 25% 0% Vanguard T Rowe Price Schwab Fidelity FIGURE 15.3 2010 Asset Allocations for Four Target 2025 Funds Sources: web sites of firms—see text.


pages: 335 words: 94,657

The Bogleheads' Guide to Investing by Taylor Larimore, Michael Leboeuf, Mel Lindauer

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asset allocation, buy low sell high, corporate governance, correlation coefficient, Daniel Kahneman / Amos Tversky, diversification, diversified portfolio, Donald Trump, endowment effect, estate planning, financial independence, financial innovation, high net worth, index fund, late fees, Long Term Capital Management, loss aversion, Louis Bachelier, margin call, market bubble, mental accounting, money market fund, passive investing, Paul Samuelson, random walk, risk tolerance, risk/return, Sharpe ratio, statistical model, survivorship bias, the rule of 72, transaction costs, Vanguard fund, yield curve, zero-sum game

Total International Stock Index Fund 3. Asset Allocation Fund 4. Total Bond Market Fund The Vanguard LifeStrategy Conservative Growth Fund has a more conservative target asset allocation of 40 percent stocks and 60 percent bonds. This fund of funds invests in five Vanguard funds: 1. Total Stock Market Index Fund 2. Total International Stock Index Fund 3. Asset Allocation Fund 4. Total Bond Market Fund 5. Short-Term Investment-Grade Bond Fund There are two other funds in the Vanguard LifeStrategy series that offer differing asset allocations. They include the LifeStrategy Moderate Growth Fund, which has a target asset allocation of 60 percent stocks and 40 percent bonds, and the LifeStrategy Income Fund with a very conservative target asset allocation of 80 percent bonds and 20 percent stocks.

We assume the investor has emergency cash savings elsewhere equal to three to twelve month's income. High-income taxpayers should consider tax exempt (municipal) bonds. READ WHAT OTHERS SAY Jack Bogle, author of Common Sense on Mutual Funds: "Asset allocation is critically important; but cost is critically important, too-All other factors pale into insignificance." Frank Armstrong, CFP, Al F, and author of The Informed Investor: "The impact of asset allocation or investment policy swamps the other (investment) decisions." William Bernstein, Ph.D., M.D., author of The Intelligent Asset Allocator and The Four Pillars of Investing: "If you really want to become proficient at asset allocation you are going to have to log off the net, turn off your computer, and go to the bookstore or library and spend several dozen hours reading books." Jonathan Clements, distinguished columnist for the Wall Street Journal and author of three financial books, Funding Your Future; TwentyFive Myths You've Got to Avoid and You've Lost it, Now What?

Gibson, CFA, CFP, author of Asset Allocation: "Asset allocation and diversification are the foundation stones of successful longterm investing." Gary Ginsler, former under-secretary of the Treasury, and Gregory Baer, assistant secretary for Financial Institutions: "Sit down and draft an asset allocation plan. If you don't know how much of your total net worth is allocated to each asset class and why, then you're making about the worst mistake in investing." AAlll Guide to Mutual Funds: "The stock market will fluctuate, but you can't pinpoint when it will tumble or shoot up. If you have allocated your assets properly and have sufficient emergency money, you shouldn't need to worry." Walter R. Good, CFA, and Roy W. Hermansen, CFA, are co-authors of Active Asset Allocation. This quote is from another of their books, Index Your Way to Investment Success: "Development of a long-term investment plan constitutes the most important single investment decision that you are likely to make."


pages: 357 words: 91,331

I Will Teach You To Be Rich by Sethi, Ramit

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Albert Einstein, asset allocation, buy low sell high, diversification, diversified portfolio, index fund, late fees, money market fund, mortgage debt, mortgage tax deduction, prediction markets, random walk, risk tolerance, Robert Shiller, Robert Shiller, shareholder value, Silicon Valley, survivorship bias, the rule of 72, Vanguard fund

This is the cost of constructing your own perfect portfolio. INVESTING ISN’T A RACE—YOU DON’T NEED A PERFECT ASSET ALLOCATION TOMORROW. Note: Once you own all the funds you need, you can split the money across funds according to your asset allocation—but don’t just split it evenly. Remember, your asset allocation determines how much money you invest in different areas. For example, if you have $250 per month and you buy seven index funds, the average person who knows nothing (i.e., most people) would split the money seven ways and send $35 to each. That’s wrong. Depending on your asset allocation, you’d send more or less money to various funds, using this calculation: (Your monthly total amount of investing money) × (Percentage of asset allocation for a particular investment) = Amount you’ll invest there. For example, if you’re investing $1,000 per month and your Swensen allocation recommends 30 percent for domestic equities, you’d calculate ($1,000) × (0.3) = $300 toward your domestic-equity fund.

But if you’re picking your own index funds, as a general guideline, you can create a great asset allocation using anywhere from three to seven funds. That would cover domestic equities, international equities, real estate investment trusts, and perhaps a small allocation to treasury bonds. Remember, the goal isn’t to be exhaustive and to own every single aspect of the market. It’s to create an effective asset allocation and move on with your life. And if you’re looking for those funds, check page 180. When you visit these websites, you’ll be able to research funds (you may have to click “Products and Services” on many of the sites) to make sure they’re low-cost and meet your asset allocation goals. YOU CANNOT JUST PICK RANDOM FUNDS AND EXPECT TO HAVE A BALANCED ASSET ALLOCATION. The first thing you want to do when picking index funds is to minimize fees.

Anyway, the little-known but true fact is that the major predictor of your portfolio’s volatility is not due, as most people think, to the individual stocks you pick, but instead your mix of stocks and bonds. In 1986, researchers Gary Brinson, Randolph Hood, and Gilbert Beebower published a study in the Financial Analysts Journal that rocked the financial world. They demonstrated that more than 90 percent of your portfolio’s volatility is a result of your asset allocation. I know asset allocation sounds like a B.S. phrase—like mission statement and strategic alliance. But it’s not. Asset allocation is your plan for investing, the way you organize the investments in your portfolio between stocks, bonds, and cash. In other words, by diversifying your investments across different asset classes (like stocks and bonds, or, better yet, stock funds and bond funds), you could control the risk in your portfolio—and therefore control how much money, on average, you’d lose due to volatility.


pages: 490 words: 117,629

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

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asset allocation, asset-backed security, 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, survivorship bias, technology bubble, the market place, transaction costs, Vanguard fund, yield curve, zero-sum game

Surprisingly, basic investment principles seem to find little support in real-world asset-allocation activity. ASSET ALLOCATION Asset-allocation decisions take center stage in most investor portfolios, because investors generally own portfolios broadly diversified within asset classes (mitigating the impact of security selection decisions) and investors generally maintain reasonably stable asset-class allocations (mitigating the impact of market-timing decisions).* With two of the three sources of return down for the count, asset allocation takes the prize as the last contender standing. Since long-term portfolio targets play such a powerful role in determining investment outcomes, sensible investors pay careful attention to establishing thoughtful asset-allocation structures. Investment maven Charley Ellis observes that investors generally fail to spend the most time and the most resources on the most important investment decisions.

The returns resulting from the active manager’s deviations relative to the benchmark represent security selection returns. Asset-allocation decisions play a central role in determining investor results. A number of well-regarded studies of institutional portfolios conclude that approximately 90 percent of the variability of returns stems from asset allocation, leaving approximately 10 percent of the variability to be determined by security selection and market timing. Another important piece of research on performance of institutional investors suggests that 100 percent of investor returns derive from asset allocation, relegating security selection and market timing to an inconsequential role.1 Careful investors pay close attention to the determination of asset class targets. Academic conclusions about the importance of asset allocation lead many students of markets to conclude that some immutable law of finance dictates the primacy of asset allocation in the investment process.

David Swensen New Haven, Connecticut March 2005 OVERVIEW 1 Sources of Return Capital markets provide three tools for investors to employ in generating investment returns: asset allocation, market timing, and security selection. Explicit understanding of the nature and power of the three portfolio management tools allows investors to emphasize the factors most likely to contribute to long-term investment goals and deemphasize the factors most likely to interfere with long-term goals. Establishing a coherent investment program begins with understanding the relative importance of asset allocation, market timing, and security selection. Asset allocation refers to the long-term decision regarding the proportion of assets that an investor chooses to place in particular classes of investments. For example, an investor with a long time horizon may opt to place 30 percent of assets in domestic equities, 20 percent of assets in foreign equities, 20 percent of assets in real estate, 15 percent of assets in inflation-indexed bonds, and 15 percent of assets in conventional bonds.


pages: 504 words: 139,137

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

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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, 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, 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

The strategic asset allocation of large institutional investors is naturally focused on market risk premiums, specifying the allocation to equities (equity risk premiums), government bonds (term premiums), corporate bonds and other risky debt (credit risk premiums), illiquid and real assets such as real estate, forestland, and infrastructure (liquidity risk premiums), as well as the cash reserves. The strategic asset allocation may also include allocations to alternative risk premiums, such as the styles discussed in this book (value, trend-following, liquidity, carry, low-risk, and quality premiums) or in terms of active investment strategies (e.g., hedge fund allocations across equity, macro, and arbitrage strategies). There are naturally many ways to choose the strategic allocation. Here we consider several methods, namely passive asset allocation, constant rebalanced asset allocation, liquidity-based asset allocation, and risk-based asset allocation. For a hedge fund that is market neutral on average, the strategic allocation can simply be viewed as a flat investment in the market, but hedge funds often use these asset allocation techniques to size their bets across strategies.

For macro investing to have a chance at success, it must either start with a strong strategic asset allocation and make modest tactical tilts or diversify across many timing strategies. In chapter 12, we see that a simple trend-following timing strategy has performed well when diversified across fifty-some equity, bond, currency, and commodity markets. Tactical Asset Allocation As discussed above, market timing means deciding the allocation to one risky market, say the equity market, which is implicitly a trade-off between cash and equities. Deciding among multiple markets is called tactical asset allocation. The classic tactical asset allocation decision is how to set the relative weights among cash, equities, and bonds. Global tactical asset allocation (GTAA) is an even more wide-ranging macro investment strategy. Here, the goal is not just to decide on the allocation across asset classes but also to consider the various global markets.

This macro investment goal can be separated into two components: (1) The long-term strategic asset allocation policy. For example, the Norwegian sovereign wealth fund (Norges Bank Investment Management) has had a benchmark portfolio (also called policy portfolio) of about 60% global equities and 40% global bonds. (2) The reallocations around the long-term weights based on current market views, called tactical asset allocation or market timing. For example, a pension fund that views the equity market as especially attractive may decide to temporarily increase its equity weight. As another example, a macro hedge fund may have a zero strategic asset allocation to the equity market so its entire investment strategy is to go long and short markets based on its tactical views. However, even a market-neutral hedge fund may use asset allocation techniques to manage its relative allocations across its various trading strategies.

Getting Started With Ledger by Rolf Schröder

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asset allocation, bitcoin, don't repeat yourself

This can be seen using --gain: $ led -X $ --gain bal Assets $ ledger --gain bal $1,500.00 Assets:Broker $ led --gain reg 42-05-28 Commodities reval ued <Revalued> 6.3 $1,500.00 $1,500.00 Asset Allocation You may want to know how your money is distributed among different asset classes. This can be easily achieved by having distinct “allocation” accounts which will serve as placeholders whenever money is put into any asset class. Using automated transactions & the virtual allocation accounts allow to get an easy overview. Consider the following: account AssetAllocation:P2PLending account AssetAllocation:Bonds account AssetAllocation:Stocks = /Receivables:P2PCompanyX/ or /Assets:P2PCompanyY/ (AssetAllocation:P2PLending) 1 = expr (commodity == 'AAPL') (AssetAllocation:Stocks) 1 = expr (commodity == 'FundsWithStocksAndBonds') (AssetAllocation:Stocks) 0.3 (AssetAllocation:Bonds) 0.7 (This could be appended to the meta.txt.) Having the above automated transactions setup will keep track of all the investments in the virtual AssetAllocation accounts, too.

Consider the following: account AssetAllocation:P2PLending account AssetAllocation:Bonds account AssetAllocation:Stocks = /Receivables:P2PCompanyX/ or /Assets:P2PCompanyY/ (AssetAllocation:P2PLending) 1 = expr (commodity == 'AAPL') (AssetAllocation:Stocks) 1 = expr (commodity == 'FundsWithStocksAndBonds') (AssetAllocation:Stocks) 0.3 (AssetAllocation:Bonds) 0.7 (This could be appended to the meta.txt.) Having the above automated transactions setup will keep track of all the investments in the virtual AssetAllocation accounts, too. One can then easily run: $ led bal [--percent] AssetAllocation to get a nice overview of the asset distribution. The advantage of this approach is that different accounts can be merged into one asset class for example. Or the other way around: Split up money from one account into different asset classes. The output will be something like $ led bal --percent AssetAllocation 100.00% AssetAllocation 17.10% Stocks 43.95% P2PLending 13.51% Bonds 25.43% Cash 30 7 The End This is the end! I hope you enjoyed the ride. If you have any questions, suggestions or general feedback, reach out for me via rolf dot schr at gmail dot com. 7.1 Contributions The following people helped getting this book finished: • Ben Finney (general feedback) • Christian Sillaber (general feedback, proof reading & Vagrant setup) • Simon Michael (general feedback & proof reading) Many thanks to them!

Getting Started With Ledger February 21, 2016 80cd614 Rolf Schröder & Others Contents Assumptions & Promises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 An introduction to Ledger 2 3 1.1 Double-entry Accounting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Ledger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 Installing Ledger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.3.1 Linux, Mac OS X & BSD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.3.2 Windows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 A first teaser . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.4 2 The Setup 7 2.1 Common files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2 Private data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2.1 Going meta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.2.2 Other files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.3 Orchestrating ecoystem & private data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.4 Tmux & Tmuxinator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.5 Your own setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3 Reports 10 3.1 Balance reports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.2 Register reports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.3 Advanced Report Filtering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.4 Sample Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 3.4.1 Answers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.5 Recurring Reports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.6 Other Reports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.7 Visualization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 4 Updating the journal 17 4.1 Cash transactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 4.2 Electronic transactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 4.2.1 The general work flow for electronic transactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Putting it all together with an example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 4.3.1 Update misc.tmp.txt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 4.3.2 Get data from NorthBank . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 4.3.3 Get data from SouthBank . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 4.3.4 Merging everything . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 4.3 1 5 Advanced 22 5.1 Formatting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 5.2 Virtual postings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 5.3 Automated Transactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 5.4 Resetting a balance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 6 Investing with Ledger 28 6.1 Dealing with commodities & market values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 6.2 Reporting gain & loss . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 6.3 Asset Allocation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 7 The End 7.1 31 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Assumptions & Promises This book is written for first timer users of Ledger (surprise!). Ledger is a command line tool and I therefore expect the reader to be familiar with the command line in general.


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

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asset allocation, Bretton Woods, British Empire, 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, 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

These two issues—how much of your overall assets you should place in stocks and how you should allocate your assets between different classes of stocks—form the core of “asset allocation.” In the 1980s, famed investor Gary Brinson and his colleagues published a pair of papers purporting to demonstrate that more than 90% of the variation in investment returns is due to asset allocation and less than 10% to timing and stock selection. These articles have been hotly contested by practitioners and academicians ever since. However, this controversy completely misses the point: it does not matter how much of your return is determined by timing or stock selection—no sane investor denies that these are important determinants of return. It’s just that you can’t control the results of timing and selection—asset allocation is the only factor you can positively impact. In other words, since you cannot successfully time the market or select individual stocks, asset allocation should be the major focus of your investment strategy, because it is the only factor affecting your investment risk and return that you can control.

But whatever allocation you settle on, the key is to stick with it through thick and thin, including rebalancing back to your target percentage on a regular basis. Step Three: Size and Value Steps one and two—the stock/bond and domestic/foreign decisions—constitute asset allocation’s heavy lifting. Once you’ve answered them, you’re 80% of the way home. If you’re lazy or just plain not interested, you can actually get by with only three asset classes, and thus, three mutual funds: the total U.S. stock market, foreign stocks, and short-term bonds. That’s it—done. However, there are a few relatively simple extra portfolio wrinkles that are worth incorporating into your asset allocation repertoire. We’ve already talked about the extra return offered by value stocks and small stocks. The diversification benefits of small stocks and value stocks are less certain. For example, during the 1973–74 bear market, value stocks did much better than growth stocks; the former lost only 23% versus 37% for the latter.

The superior expected return and risk of a highly diversified portfolio come at the price of tracking error—the risk that your portfolio will significantly lag the S&P 500, and thus the portfolios of your friends and neighbors—for years at a time, as happened during the late 1990s. CHAPTER 4 SUMMARY 1. Past portfolio performance is only weakly predictive of future portfolio behavior. It is a mistake to design your portfolio on the basis of the past decade or two. 2. Your exact asset allocation is a function of your tolerance for risk, complexity, and tracking error. 3. The most important asset allocation decision revolves around the overall split between risky assets (stocks) and riskless assets (short-term bonds, bills, CDs, and money market funds). 4. The primary diversifying stock assets are foreign equity and REITs. The former should be less than 40% of your stock holdings, the latter less than 15%. 5. Exposure to small stocks, value stocks, and precious metals stocks is worthwhile, but not essential.


pages: 537 words: 144,318

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

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Albert Einstein, Asian financial crisis, asset allocation, asset-backed security, backtesting, banking crisis, Bernie Madoff, Black Swan, Bretton Woods, BRICs, British Empire, business process, 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, 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, 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

Tactical asset allocation has worked for us both in the model sense and in the discretionary sense. But then again, we are small and nimble, so we can do it. There are many models of tactical asset allocation that seem to work, and I have discussed them at Drobny Conferences. We have done momentum models on returns, on correlations, and have even run efficient frontiers that, using ETFs, generate returns very similar to what Yale has generated through its asset allocation process and successful manager selection. So I believe that tactical asset allocation works, though it is very difficult to make it work for very large investors like CalPERS or for the entire investment industry. While we think about valuation, we do not actually utilize valuation-driven models for asset allocation. Valuation-driven tactical asset allocation models need a much longer time frame because of the difficulty of forecasting when assets will actually revert to fair value.

But when a true crisis hits and the markets collapse, you have the protection when you need it. Does asset allocation work in a world where extreme events happen more often than predicted? Asset allocation works if you put in the correct forward-looking returns. If you knew what the returns were going to be, the models would come back with perfect portfolios. The problem is not with asset allocation but with figuring out what returns and what correlations to use. Should you be using 30-year correlations when you are nervous about the one week when all markets collapse simultaneously? Should you be using long-term forecasts for equity risk premia when the next equity risk premium could be negative? We use tactical asset allocation models to manage a portion of our capital and help our research process. These models help in two ways.

I have been running my personal account since 1997, during which time my average cash balance has been 25 percent, whereas the high was probably 90 percent. To an absolute return investor, cash is an essential asset. When other assets have negative returns forecast over the next 6 or 12 months, there is no reason to not hold a low return cash portfolio. As an absolute return macro manager, I believe in tactical asset allocation and that clearly distinguished my approach from the Endowment Model, where asset allocation is never done tactically. The Endowment Model’s core approach consists of a long-term process where equity-like returns are being generated in a diversified portfolio. How do you value cash? The prevailing wisdom looks at cash on a historical basis, which completely neglects the inherent opportunity costs associated with a lack of cash. By this I mean simply that cash affords you flexibility; if you have cash, you can allocate that cash when attractive opportunities arise.

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

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Asian financial crisis, asset allocation, backtesting, 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

Results demonstrated that CTAs bring diversification as long as the asset allocation environment is constrained. This diversification ability clearly increases the lower the weight threshold is (the stricter the constraints are) and if the included assets are only standard assets. Aside from the demonstration of the CTAs’ added value, the rolling window analyses illustrate the time variability of the efficient frontiers. This finding was expected because the input factors are themselves evolving through time, proving the necessity of using dynamic asset allocation. Moreover, the analyses also reveal that CTAs did not systematically improve portfolio returns over the period 1996 to 2002. More generally, the three-dimensional graphs presented are one of the first attempts at using surfaces as a visualization and assessment tool for asset allocation. The frameworks prove interesting for decision making, understanding efficient portfolio constructions, and temporal dynamics.

TABLE 20.2 Correlations Across CTA and Traditional Asset Classes, January 1990 to February 2003 CTA QU Index CTA QU Index SCM Bond Index S&P/TSX S&P 500 MSCI EAFE 1 0.20 −0.12 −0.13 −0.19 SCM S&P/ TSX S&P 500 1 0.32 0.26 0.20 1 0.75 0.66 1 0.70 MSCI EAFE 1 363 Incorporating CTAs into the Asset Allocation Process INCORPORATING CTA TO THE ASSET ALLOCATION PROCESS In this section, we show the results obtained by applying the mean-VaR framework explained previously. We compute the efficient frontier and the optimal portfolio allocation for a Canadian pension fund assuming that the portfolio manager has a VaR limit, that is, the manager does not want to lose more than a specified amount each month, with a specified probability (typically 1 or 5 percent). The individual asset classes can vary within specific limits. As a result, a relatively conservative asset allocation was chosen to match the allocations of conservative investors, pension funds, and institutions. The weightings of individual asset classes are then changed within the permitted margins to minimize the normal VaR (see Table 20.3).

Using these benchmark assets, the author estimates the efficiency gain or loss each CTA produces and analyzes the robustness of this kind of efficiency measurement with respect to the number of moments used. Chapter 17 aims at providing an overview of the industry and to quantify its added value when included in portfolios (mean/variance optimization). Different statistics and asset allocations studies are displayed within a fixed or dynamic framework. A dynamic framework takes into account time evolutions. On the asset allocation side, it then implies working in a three-dimensional environment (mean/variance/time framework) and dealing with efficient surfaces rather than efficient frontiers. Chapter 18 examines whether CTA percent changes in NAVs follow random walks. Monthly data from January 1994 to December 2000 are tested 275 276 PROGRAM EVALUATION, SELECTION, AND RETURNS for nonstationarity and random walk with drift, using the Augmented DickeyFuller test.


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The Clash of the Cultures by John C. Bogle

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asset allocation, 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, 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

The typical return projection is 8 percent, with a few plans—corporate and local government alike—as high as 9 percent and a few as low as 7 percent, or even slightly less. (Berkshire Hathaway is using a 6.9 percent assumption.) Where do these estimates come from? Well, here is what one large corporation tells us: “We consider current and expected asset allocations, as well as historical and expected returns on various categories of plan assets . . . evaluating general market trends as well as key elements of asset class returns such as expected earnings growth, yields and spreads. Based on our analysis of future expectations of asset performance, past return results, and our current and expected asset allocations, we have assumed an 8.0 percent long-term expected return on those assets” (italics added, General Electric Annual Report, 2010). Such disclosure has become sort of annual-report boilerplate. All well and good, but, as they say, let’s add some “granularity” (a word I don’t much care for), making some assumptions that are arbitrary but not unrealistic.

The shift towards defined contribution retirement plans has essentially thrust the head of each participating household into the role of pension plan manager, a role for which they are not properly prepared and are often reluctant to assume. As a result, retirement savers make many of the mistakes already discussed—not saving enough, being either too conservative or too aggressive in their asset allocation, taking loans from a 401(k), cashing out early—simply because they’ve received inadequate preparation for these critical investment decisions. The fund industry has not helped, marketing their hottest funds and giving inadequate attention to the critical role played by asset allocation. The New Pension Plan Given the tenuous funding of DB plans, the widespread failures in the existing DC plan structure—including both 401(k) plans and IRAs—we ought to carefully consider and then implement changes that move us to a retirement plan system that is simpler, more rational, and less expensive.

See Defined benefit (DB) pension plans; Defined contribution (DC) pension plans; Retirement system “People-who-live-in-glass-houses” syndrome PIMCO (Pacific Investment Management Company) Pioneer Fund Politics Portfolio managers, experience and stability of Portfolio turnover: actively managed equity funds exchange traded funds index funds mutual funds Stewardship Quotient and Positive Alpha Press, financial Pricing strategy PRIMECAP Management Company Principals Product, as term Product proliferation, in mutual fund industry Product strategy Profit strategy Proxy statement access by institutional investors, proposed Proxy vote disclosure by mutual funds Prudent Man Rule Public accountants Putnam, Samuel Putnam Management Company Quantitative techniques Random Walk Down Wall Street, A (Malkiel) Rappaport, Alfred Rating agencies Real market Redemptions, shareholder Regulatory issues REIT index fund Retirement accumulation, inadequate Retirement system: about Ambachtsheer, Keith, on asset allocation and investment selection components conflicts of interest costs, excessive current flaws in flexibility, excessive 401(k) retirement plans ideal investor education, lack of longevity risk, failure to deal with mutual funds in New Pension Plan, The pensions, underfunded recommendations retirement accumulation, inadequate savings, inadequacy of “Seven Deadly Sins,” speculation and stock market collapse and value extracted by financial sector Returns: asset allocation and balanced funds defined benefit pension plans projections of equity mutual funds exchange traded funds investment large-cap funds market mutual fund industry speculative Wellington Fund Reversion to the mean (RTM) Riepe, James S.


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The Simple Path to Wealth: Your Road Map to Financial Independence and a Rich, Free Life by J L Collins

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asset allocation, Bernie Madoff, compound rate of return, diversification, financial independence, full employment, German hyperinflation, index fund, money market fund, nuclear winter, passive income, payday loans, risk tolerance, Vanguard fund, yield curve

~5% Cash: We hold ours in our local bank. You can fine-tune these allocations to your own personal considerations. Want a smoother ride? Willing to accept a potentially lower long-term return and slower wealth accumulation? Just increase the percentage in VBTLX. Comfortable with volatility? Want more growth? Add more to VTSAX. Now that we’ve introduced this idea of asset allocation, we’ll explore it a bit more next. Chapter 14 Selecting your asset allocation Life is balance and choice. Add more of this, lose a little of that. When it comes to investing, that balance and choice is informed by your temperament and goals. Financial geeks like me are the aberration. Sane people don’t want to be bothered. My daughter helped me understand this at about the same time I was finally understanding that the most effective investing is also the simplest.

Investing in a raging bull (or bear) market Part II: How to harness the world’s most powerful wealth-building tool 6. There’s a major market crash coming!!!! and even famous economists can’t save you 7. The market always goes up 8. Why most people lose money in the market 9. The Big Ugly Event 10. Keeping it simple: Considerations and tools 11. Index funds are really just for lazy people, right? 12. Bonds 13. Portfolio ideas to build and keep your wealth 14. Selecting your asset allocation 15. International funds 16. TRFs: The simplest path to wealth of all 17. What if you can’t buy VTSAX? Or even Vanguard? 18. What is it about Vanguard anyway? 19. The 401(k), 403(b), TSP, IRA and Roth buckets 20. RMDs: The ugly surprise at the end of the tax-deferred rainbow 21. HSAs: More than just a way to pay your medical bills 22. Case study: Putting The Simple Path to Wealth into action 23.

Until you can be absolutely certain that you can watch your wealth get cut in half and still stay the course, the answer is no. Until you are comfortable with the risks that come with the rewards you seek, the answer is no. In the end, only you can decide. Fortunately, investing doesn’t have to be an all or nothing proposition. If you are willing to give up some performance, there are ways to smooth out the ride a bit. It is done with asset allocation, which we’ll discuss in Chapter 14. Note: In referencing the market’s performance in this chapter, you may have noticed I jump between using the Dow and the S&P as the indexes. I prefer the S&P because it is broader and therefore a bit more precise. But the Dow goes back further in history and is more useful (and available) for the long view. If you overlay their charts over time, they track together with remarkable consistency, making them, for our purposes, indistinguishable.


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Nudge: Improving Decisions About Health, Wealth, and Happiness by Richard H. Thaler, Cass R. Sunstein

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Al Roth, Albert Einstein, asset allocation, availability heuristic, call centre, Cass Sunstein, choice architecture, continuous integration, Daniel Kahneman / Amos Tversky, desegregation, diversification, diversified portfolio, endowment effect, equity premium, feminist movement, fixed income, framing effect, full employment, George Akerlof, index fund, invisible hand, late fees, libertarian paternalism, loss aversion, Mahatma Gandhi, Mason jar, medical malpractice, medical residency, mental accounting, meta analysis, meta-analysis, Milgram experiment, money market fund, pension reform, presumed consent, profit maximization, rent-seeking, Richard Thaler, Right to Buy, risk tolerance, Robert Shiller, Robert Shiller, Saturday Night Live, school choice, school vouchers, transaction costs, Vanguard fund, Zipcar

Most teachers know that students tend to sit in the same seats in class, even without a seating chart. But status quo bias can occur even when the stakes are much larger, and it can get us into a lot of trouble. For example, in retirement savings plans, such as 401(k)s, most participants pick an asset allocation and then forget about it. In one study conducted in the late 1980s, participants in tiaa-cref, the pension plan of many college professors, the median number of changes in the asset allocation of the lifetime of a professor was, believe it or not, zero. In other words, over the course of their careers, more than half of the participants made exactly no changes to the way their contributions were being allocated. Perhaps even more telling, many married participants who were sin- BIASES AND BLUNDERS gle when they joined the plan still have their mothers listed as their beneficiaries!

One company switched from an opt-in regime to active decisions and found that participation rates increased by about 25 percentage points.8 A related strategy is to simplify the enrollment process. One study tested this idea by analyzing a simplified enrollment form.9 New employees were handed enrollment cards during orientation with a “yes” box for joining the plan at a 2 percent savings rate and a preselected asset allocation. Employees did not have to spend time choosing a savings rate and asset allocation; they could just check the “yes” box for participation. As a result, participation rates during the first four months of employment jumped from 9 percent to 34 percent. These simplified enrollment procedures are very much in the spirit of the “channel factors” we mentioned in Chapter 3. People really do want to join the plan, and if you dig a channel for them to slide down that removes the seemingly tiny barriers that are getting in their way, the results can be quite dramatic.

These low fees for the index funds helped keep *In fact, the percentage of active choosers has declined steadily, from 17.6 percent in 2001, the first year after the launch. 149 150 MONEY Table 9.1 Comparison of the default fund and the mean actively chosen portfolio Asset allocation Default (%) Mean actively chosen portfolio (%) Equities Sweden Americas Europe Asia Fixed-income securities (bonds) Hedge funds Private equity 82 17 35 20 10 10 4 4 96.2 48.2 23.1 18.2 6.7 3.8 0 0 Indexed 60 4.1 Fee Returns for the first three years Returns through July 2007 0.17 29.9 21.5 0.77 39.6 5.1 Note: The table compares the default fund and the mean actively chosen portfolio. The data on the asset allocations are from data on funds’ holdings from Morningstar. Fee is the yearly expense ratio as a percentage of fund assets. Ex post performance is returns over a three-year postreform period (October 31, 2000 through October 31, 2003).

The Handbook of Personal Wealth Management by Reuvid, Jonathan.

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asset allocation, banking crisis, BRICs, 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

Having made an appropriate choice of wealth manager, the most well-served investor will be easily able to consult the full apparatus and make an informed view on the correct asset allocation approach. This consultation will at times veer towards art and at others be scientific, but the balance should be appropriate. Regardless, transparent accessibility to this underlying information becomes a competitive differentiator that improves the scope for appropriate investment implementation. In short, while it is important to get forecasts – and any subsequent investment ឣ 16 PORTFOLIO INVESTMENT _________________________________________________ advice following them – right, it is equally important to demonstrate to the investor how and why the approach taken to arrive at any conclusions is reached. These days, the vast majority of advisers understand the merits of a defined longer-term asset allocation policy. Typically, this involves relaying the fact that a strategic asset allocation strategy explains most of the variability in returns over the longer term.

The expected portfolio return, based upon indices (used as replication strategies), may be different from the behaviour of the actual portfolio. This can be seen by observing the difference between the performances of two portfolios constructed using an identical asset allocation in the Figure 1.2.3 example below. 2.00% 1.00% Tracking error -40.00% 0.00% Source: Citi Private Bank as at December 2008 This figure is for discussion purposes only and for use in the context of this particular chapter. Past performance is no indication of future results. Real results may vary. Figure 1.2.3 Quantifiably different: the active portfolio relative to the asset allocation an index representative portfolio The pricing behaviour of the two portfolios shown in the figure is clearly correlated but is still staggeringly different. The tracking error demonstrates how closely the active portfolio follows the portfolio constructed at index-level.

This is done by transforming the way donations are made and charitable funds are managed. CAF’s core activity is to provide innovative financial services to charities and their supporters. Philip Watson assumed the position of Head of Investment Analysis and Advisory Group (IAAG) at Citi Private Bank EMEA in April 2006, having previously been a senior portfolio analyst since 2003. He oversees a team of 12 professionals who manage the asset allocation and portfolio construction of the Bank’s high-net-worth clients. The work of IAAG is a competitive differentiator for Citi Private Bank, contributing to its intellectual leadership and forming the cornerstone of investment conversation with clients. Philip has been with Citi for eight years. His previous assignments have included working for the Corporate and Investment Bank in equity derivatives, where he performed diverse roles including senior profit and loss analysis, risk management and warrants trading. 1 Introduction In 2008 conventional private investor thinking was turned upside down following the ‘credit crunch’ and the ensuing stream of dismal revelations of imprudent bank lending, financial products based on the packaging of toxic debt and inadequate financial sector regulation.


pages: 44 words: 13,346

Extreme Early Retirement: An Introduction and Guide to Financial Independence (Retirement Books) by Clayton Geoffreys

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asset allocation, dividend-yielding stocks, financial independence, index fund, passive income, risk tolerance

It may work that way at times, but it is even better if you diversify or spread your funds into different types of investments. If your investment is only focused on a few stocks, then obviously your return is heavily reliant on how those stocks or the entire stock market performs. One thing you can do is give more attention to your asset allocation. This is where you divide your funds into different types of investments, and more often than not, asset allocation is a decisive factor that will formulate the outcome of your investment’s return. You have direct control of your asset allocation, so if for example you want to have 50% on stocks, 40% on bonds, and 10% on real estate, you can do that at your own expense. Another thing is to keep your costs at a low level because there is absolutely no reason for you to be investing at a high cost when you can comparatively invest elsewhere at a much lower cost.

With index funds, you also know exactly what it is you are investing into, unlike actively-managed funds where the portfolio manager might begin investing into certain stocks and at some point engage in another type of investment, hence, affecting your asset allocation. In this case, you get completely thrown off course with your asset allocation and it becomes more difficult to formulate a solution to balance the scales and continue raking in returns. Just remember, if you are engaged with actively-managed funds and you decide to invest in other things or sell a few of your investments due to your asset allocation being thrown off course, you will incur taxes and trading fees. On the other hand, index funds provide great consistency and you save more money, allowing room for further investments. Diversification is another reason why you should get started in index investing because the concept is relatively easy to grasp.

However, other early retirees suggest that 25 or 30 is a safe number because extreme early retirement is all about being financially independent. You want to maximize your funds as much as possible after which you can invest from those funds. Basically, the earnings you get from annual interest will continue to grow and that is the reason why you want to invest as early in your life as possible. Depending on your asset allocation, you may or may not see that much of a difference, but again, in a few years' time you will have enough funds in circulation from which you gain the momentum to invest again. Finally, you must always make it a point to be physically or at least mentally active in your retired life to avoid boredom. Be creative and take pleasure in the retired life which you worked so hard for. Final Word/About the Author Usually I write works around sports to learn more about influential athletes in the hopes that from my writing, you the reader can walk away inspired to put in an equal if not greater amount of hard work and perseverance to pursue your goals.


pages: 130 words: 11,880

Optimization Methods in Finance by Gerard Cornuejols, Reha Tutuncu

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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, Y2K

Given these considerations the robust optimization problem given in (OROP) takes the following form max{ min µT x − lxT Qx} (7.11) x∈X (µ,Q)∈U which is equivalent to minx∈X {max(µ,Q)∈U −µT x + lxT Qx}. This problem can be ex- 90CHAPTER 7. ROBUST OPTIMIZATION MODELS AND TOOLS IN FINANCE pressed as a saddle-point problem and be solved using the technique outlined in [6]. 7.3.2 Robust Asset Allocation: A Case Study This material in this section is adapted from the article [16]. 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.

Technical report, Bilkent University, Ankara, Turkey, 2001. [12] R. T. Rockafellar and S. Uryasev. Optimization of conditional value-at-risk. The Journal of Risk, 2:21–41, 2000. [13] W. F. Sharpe. Determining a fund’s effective asset mix. Investment Management Review, pages 59–69, December 1988. [14] W. F. Sharpe. Asset allocation: Management style and performance measurement. Journal of Portfolio Management, pages 7–19, Winter 1992. [15] W.F. Sharpe. The Sharpe ratio. Journal of Portfolio Management, Fall:49–58, 1994. [16] R. H. Tütüncü and M. Koenig. Robust asset allocation. Technical report, Department of Mathematical Sciences, Carnegie Mellon University, August 2002. To appear in Annals of Operations Research. [17] S. Uryasev. Conditional value-at-risk: Optimization algorithms and applications. Financial Engineering News, 14:1–6, 2000.

Tütüncü Optimization in Finance Advanced Lecture on Mathematical Science and Information Science I Dept. of Mathematical and Computing Sciences Tokyo Institute of Technology Department of Mathematical Sciences Carnegie Mellon University 2003 Contents Preface xi 1 Introduction 1.1 Continuous Optimization: A Brief Classification 1.1.1 Linear Optimization . . . . . . . . . . . 1.1.2 Quadratic Optimization . . . . . . . . . 1.1.3 Conic Optimization . . . . . . . . . . . . 1.2 Optimization with Data Uncertainty . . . . . . 1.2.1 Stochastic Optimization . . . . . . . . . 1.2.2 Robust Optimization . . . . . . . . . . . 1.3 Financial Mathematics . . . . . . . . . . . . . . 1.3.1 Portfolio Selection and Asset Allocation 1.3.2 Pricing and Hedging of Options . . . . . 1.3.3 Risk Management . . . . . . . . . . . . . 1.3.4 Asset Liability Management . . . . . . . . . . . . . . . . . . . 2 Linear Programming: Theory and Algorithms 2.1 The Linear Programming Problem . . . . . . . . 2.2 Duality . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Optimality Conditions . . . . . . . . . . . . . . . 2.4 The Simplex Method . . . . . . . . . . . . . . . . 2.4.1 Basic Solutions . . . . . . . . . . . . . . . 2.4.2 Simplex Iterations . . . . . . . . . . . . . 2.4.3 The Tableau Form of the Simplex Method 2.5 Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 LP Models and Tools in Finance 3.1 Derivative Securities and The Fundamental Theorem of 3.1.1 Replication . . . . . . . . . . . . . . . . . . . . 3.1.2 Risk-Neutral Probabilities . . . . . . . . . . . . 3.2 Arbitrage Detection Using Linear Programming . . . . 3.3 Risk Measures: Conditional Value-at-Risk . . . . . . . iii . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .


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

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Albert Einstein, asset allocation, asset-backed security, Brownian motion, business process, 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, equity premium, fixed income, implied volatility, index fund, intangible asset, interest rate swap, inventory management, London Interbank Offered Rate, margin call, market fundamentalism, 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

Related Terms: • Balance Sheet • Depreciation • Tangible Asset • Current Assets • Intangible Asset 14 The Investopedia Guide to Wall Speak Asset Allocation What Does Asset Allocation Mean? An investment strategy that aims to balance risk and reward by spreading investments across three main asset classes—equities, bonds, and cash—in accordance with an individual’s goals, risk tolerance, and investment horizon. Historically, different asset classes have varying degrees of risk and return and therefore behave differently over time. Investopedia explains Asset Allocation There is no simple formula to determine the proper asset allocation for every individual. However, the consensus among financial professionals is that asset allocation is one of the most important investment components. In other words, individual securities selection is secondary to the way an investor allocates investments across stocks, bonds, and cash.

Investopedia explains Market Capitalization If a company has 35 million shares outstanding with a current share price of $100, the company’s market capitalization is $3.5 billion (35,000,000 × $100 per share). Company size is a basic determinant of asset allocation and risk-return parameters for stocks and stock mutual funds. The term should not be confused with a company’s “capitalization,” which is a financial accounting term that refers to the sum of a company’s shareholders’ equity plus its long-term debt. The stocks of large, medium, and small companies are referred to as large-cap, mid-cap, and small-cap, respectively. In general, market 174 The Investopedia Guide to Wall Speak cap breakdowns look like this: large cap: $10 billion or more, mid cap: $2 billion to $10 billion, small cap: less than $2 billion. Related Terms: • Asset Allocation • Large Cap—Big Cap • Small Cap • Index • Mid Cap Market Economy What Does Market Economy Mean?

Investopedia explains Modern Portfolio Theory (MPT) According to the theory, it is possible to construct an efficient frontier of optimal portfolios that offers the maximum possible expected return for a specific level of risk. This theory was pioneered by Harry Markowitz in his paper “Portfolio Selection,” which was published in 1952 in the Journal of Finance. The four basic steps involved 182 The Investopedia Guide to Wall Speak in portfolio construction are (1) security valuation, (2) asset allocation, (3) portfolio optimization, and (4) performance measurement. Related Terms: • Asset Allocation • Correlation • Efficient Market Hypothesis—EMH • Mutual Fund • Risk Modified Duration What Does Modified Duration Mean? A formula that expresses the   measurable change in the   Macaulay Duration  Modified Duration =  value of a security in response    YTM  to a change in interest rates. It 1 =     n  is calculated as follows: Where n = number of coupon periods per year, YTM = the bond’s yield to maturity.


pages: 368 words: 145,841

Financial Independence by John J. Vento

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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 235 26/02/13 2:51 PM c09.indd 236 Exhibit 9.3 Investment Growth Based on Rates of Return 1980 to 2012 11.0% 75% Stocks and 25% Bonds 50% Stocks and 50% Bonds 10.0% 20% Stocks and 80% Bonds <Lower Return 236 - Rate of Return - Higher Return> 100% Stock 100% Bonds 9.0% 10.0 11.0 12.0 <Less Volatility 13.0 14.0 - Risk 15.0 - 16.0   More Volatility> 17.0 18.0 26/02/13 2:51 PM Managing Your Investments 237 Asset Allocation and Rebalancing5 Asset allocation is an investment strategy that provides a systematic approach to diversification that may help you establish the most efficient blend of assets based on your particular risk tolerance level and investing time horizon. Studies have shown that asset allocation is more important than all other factors in managing your investments. Although it is helpful to work with a professional money manager who has a proven successful track record, selecting the right balance of asset classes is more important. Asset allocation seeks to control investment risk by diversifying a portfolio among the four major asset classes: 1. Cash includes currency, coins, checking accounts, savings accounts, money market accounts, and certificates of deposit. 2.

It is very important to keep in mind that there is no one approach that will fit every individual investor. Now that you have selected your ideal asset allocation model based on your acceptable risk tolerance, it is important to monitor and maintain this allocation. Rebalancing your portfolio is one of the essential aspects of maintaining a successful investment strategy over time. Rebalancing requires you to analyze the changes in your asset allocation model periodically and make changes in an attempt to bring you back to your original allocation. You do this by selling and buying various investments within each of the asset classes, to maintain your established asset allocation. Suppose the original asset allocation model you established included 1 percent cash, 28 percent stock, and 71 percent bonds. During a period of falling interest rates, your bond values increased to represent 76 percent of your portfolio and your stock values now only represent 23 percent of your overall portfolio.

The basic idea is that while one asset class may be increasing in value one or more of the others may be decreasing. Therefore, asset allocation and diversification may help you ride out market fluctuations and protect your portfolio from a major loss in any one asset class. They may also provide you with the staying power and control over your emotions even after a big downturn in the market. However, it is important to understand that asset allocation and diversification do not guarantee against loss. They are simply strategies that may help smooth the ride to your financial independence, point X. It is fundamental to find a mixture of asset classes with the highest potential return within your risk profile. Exhibit 9.4 shows seven sample asset allocation models that can be used as a guide to fit into your own risk tolerance level. There are, of course, an unlimited number of variations to these sample models. 5 Before you rebalance your portfolio, you should consider whether the method of rebalancing you decide to use will trigger transaction fees or tax consequences.

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

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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 process, 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 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 colleague, Sébastien Page, and I performed the analysis using bootstrap simulations of available returns and discovered that security selection was overwhelmingly more important than asset allocation.14 This outcome, which we did not anticipate, provoked considerable debate among academics and practitioners. As this debate intensified, I reexamined the BHB methodology and discovered it was specious for reasons other than its reliance on realized returns. I contrived an experiment to demonstrate its fundamental flaw. I hypothesized a world in which all asset classes had the same performance, but within each asset class the performance of individual securities varied significantly. In this hypothetical world, security selection explained 100 percent of the difference in the performance among funds, while asset allocation had no impact whatsoever. I essentially created a world with a single asset class, thus rendering the asset allocation decision irrelevant.

Reasonably soon after my arrival at Equitable, I managed to land a job in the Investment Advisory Department, which managed the asset allocation of Equitable’s pension fund clients. This group determined how to allocate the funds across the various separate accounts that were invested in money market instruments, publicly traded bonds, direct placement bonds, large stocks, small stocks, and real estate. It was here that I first encountered mean-variance analysis, which upon reflection marks the beginning of my career as a quant. By this time, I had also begun pursuit of an MBA degree by studying evenings at New York University, so I was able to learn about mean-variance analysis both as a student and by experience. With the help of Chester Spatt,1 then an undergraduate at Princeton who consulted with us, equitable developed one of the industry’s first mean-variance asset allocation models, and we added a capability to perform risk analysis with assistance from NYU professors Aaron Tenenbein, Ned Elton, and Marty Gruber.

These experiments showed that mean-variance optimization, at least in two very typical applications, is robust to estimation error when measured appropriately.11 The Hierarchy of Investment Choice. Peter Bernstein asked me to tackle the question of the relative importance of asset allocation and security selection, so I did. It occurred to me that the obvious way to address the issue was to simulate returns by holding fixed one decision and varying the other. Then I could determine which decision generated more dispersion in wealth. This experiment would allow me to measure the dispersion in performance that arises naturally by engaging in a particular investment activity. Other approaches for sorting out the relative importance of asset allocation and security selection, such as Brinson, Hood, and Beebower (BHB)12 and Ibbotson and Kaplan13 focused on the realized returns of managed portfolios; consequently, these studies failed to disentangle investment behavior from investment opportunity.


pages: 447 words: 104,258

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

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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

The simplest way to incorporate this effect is by splitting the asset allocation contribution in two parts, one reflecting the currency performance itself, and the second reflecting the actual asset allocation contribution, that is, the original one, minus the currency effect: To determine the currency attribution effect, we have first, to define currency returns rci, equal to 0 for each of the portfolio lines or sub-sets quoted in the portfolio currency, and, for the other ones, equal to the appreciation or depreciation of other currencies vis-à-vis the portfolio currency; this allows to compute the global currency return rcB of the benchmark, as follows: second, to compute, for each portfolio line or sub-set, the currency attribution effect, by using the same formula as for the asset allocation attribution (Eq. 14.3), but applied here on the currency impact rcBi − rcB: and deduct this amount from the original asset allocation contribution, for obtaining the actual asset allocation contribution. Coming back to our example, the portfolio is in USD, but the Nikkei sub-set has made its performance primarily in JPY, and during the year 2005, the JPY has depreciated by 12.69% against the USD. So that, for the Nikkei portfolio subset, the actual asset allocation contribution has to be reduced by the corresponding (negative, here) currency contribution. In Figure 14.9 we see that the sum of attribution effects is unchanged, but the actual asset allocation contribution is of 3.48% instead of 2.21%: the reduction to 2.21% is due to the loss on the currency.

The second component of the attribution focuses on the returns (invested at different dates than for the benchmark, the portfolio returns are different), and is called “stock selection attribution”: the portfolio manager's skill can be quantified about this aspect, by considering the impact of the portfolio returns on the benchmark weights: Finally, we have to add the interaction of both effects: a different weighting can be associated to a better or worst return, depending on the investment date:3 Applied to the above example, we obtain the result in Figure 14.8, showing that the portfolio manager's skill was mainly noticeable in the stock selection in the Nasdaq and Nikkei sub-sets, and in the Nikkei asset allocation. Figure 14.8 Result of the portfolio manager's choices Impact of the Currencies on the Performance Attribution If the portfolio in invested in one or several currencies other than the portfolio currency, in these cases the appreciation or depreciation of a currency of an asset (or a sub-set of the portfolio) is affecting the portfolio performance and therefore the performance attribution. The simplest way to incorporate this effect is by splitting the asset allocation contribution in two parts, one reflecting the currency performance itself, and the second reflecting the actual asset allocation contribution, that is, the original one, minus the currency effect: To determine the currency attribution effect, we have first, to define currency returns rci, equal to 0 for each of the portfolio lines or sub-sets quoted in the portfolio currency, and, for the other ones, equal to the appreciation or depreciation of other currencies vis-à-vis the portfolio currency; this allows to compute the global currency return rcB of the benchmark, as follows: second, to compute, for each portfolio line or sub-set, the currency attribution effect, by using the same formula as for the asset allocation attribution (Eq. 14.3), but applied here on the currency impact rcBi − rcB: and deduct this amount from the original asset allocation contribution, for obtaining the actual asset allocation contribution.

Index 4-moments CAPM actual (ACT) number of days AI see Alternative Investments “algorithmic” trading Alternative Investments (AI) American options bond options CRR pricing model option pricing rho amortizing swaps analytic method, VaR annual interest compounding annualized volatility autocorrelation corrective factor historical volatility risk measures APT see Arbitrage Pricing Theory AR see autoregressive process Arbitrage Pricing Theory (APT) ARCH see autoregressive conditional heteroskedastic process ARIMA see autoregressive integrated moving average process ARMA see autoregression moving average process ask price asset allocation attribution asset swaps ATM see at the money ATMF see at the money forward options at the money (ATM) convertible bonds options at the money forward (ATMF) options attribution asset allocation performance autoregression moving average (ARMA) process autoregressive (AR) process autoregressive conditional heteroskedastic (ARCH) process autoregressive integrated moving average (ARIMA) process backtesting backwardation basket CDSs basket credit derivatives basket options BDT see Black, Derman, Toy process benchmarks Bermudan options Bernardo Ledoit gain-loss ratio BGM model see LIBOR market model BHB model (Brinson’s) bid price binomial distribution binomial models binomial processes, credit derivatives binomial trees Black, Derman, Toy (BDT) process Black and Karasinski model Black–Scholes formula basket options beyond Black–Scholes call-put parity cap pricing currency options “exact” pricing exchange options exotic options floor pricing forward prices futures/forwards options gamma processes hypotheses underlying jump processes moneyness sensitivities example valuation troubles variations “The Black Swan” (Taleb) bond convexity bond duration between two coupon dates calculation assumptions calculation example callable bonds in continuous time duration D effective duration forwards FRNs futures mathematical approach modified duration options physical approach portfolio duration practical approach swaps uses of duration bond futures CFs CTD hedging theoretical price bond options callable bonds convertible bonds putable bonds bond pricing clean vs dirty price duration aspects floating rate bonds inflation-linked bonds risky bonds bonds binomial model CDSs convexity credit derivatives credit risk exotic options forwards futures government bonds options performance attribution portfolios pricing risky/risk-free spot instruments zero-coupon bonds see also bond duration book value method bootstrap method Brinson’s BHB model Brownian motion see also standard Wiener process bullet bonds Bund (German T-bond) 10-year benchmark futures callable bonds call options call-put parity jump processes see also options Calmar ratio Capital Asset Pricing Model (CAPM) 4-moments CAPM AI APT vs CAPM Sharpe capitalization-weighted indexes capital market line (CML) capital markets caplets CAPM see Capital Asset Pricing Model caps carry cash and carry operations cash flows cash settlement, CDSs CBs see convertible bonds CDOs see collateralized debt obligations CDSs see credit default swaps CFDs see contracts for difference CFs see conversion factors charm sensitivity cheapest to deliver (CTD) clean prices clearing houses “close” prices CML see capital market line CMSs see constant maturity swaps Coleman, T.


pages: 519 words: 118,095

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

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Airbnb, asset allocation, bank run, buy low sell high, car-free, Community Supported Agriculture, delayed gratification, diversification, diversified portfolio, estate planning, Firefox, fixed income, full employment, 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, traveling salesman, Vanguard fund, web application, Zipcar

If you know why you're investing and have a long-term plan, it's easier to avoid making rash decisions that can lower your returns. Financial advisers suggest you create an investment policy statement, or IPS, which is simply your target asset allocation (see the Note below) and instructions to yourself for how to set and maintain it. Note Asset allocation is the way your money is divided among your different investments; it's just a fancy way of saying "the things you've invested in." The classic example is the basic 60/40 split: 60% invested in stocks and 40% in bonds. To learn more about asset allocation, read the SEC's "Beginner's Guide to Asset Allocation" at http://tinyurl.com/SEC-assets. You can learn more here: http://tinyurl.com/GRS-alloc. In other words, your IPS is a blueprint for your investments. It's a plan to help you build your future.

In that case, you might consider a fund like Fidelity Freedom 2035, which includes a mix of investments that make sense for people who plan to retire in 2035 (when they'll be around 65). Lifecycle funds have a lot of things going for them. For example, you get: Automatic asset allocation, since lifecycle funds include various asset classes. International exposure. Lifecycle funds are collections of mutual funds, including some international investments. Automatic rebalancing. Fund managers adjust lifecycle funds' asset allocation to make them more conservative as you get older. The main drawback of lifecycle funds is that you don't have any control over them. For example, if you want the international portion of your stocks to be 50% (or more), you're out of luck. Some people are okay with that, but the lack of control drives other people crazy.

Minimum investment requirements create another problem, too: When you first invest, you probably won't be able to afford every fund in your target portfolio. So you may have to start with just one fund instead of jumping right into your plan for three or eight, but that's okay. When you're just beginning to invest, your contributions are far more important than your asset allocation (Know Your Goals). So don't sweat it if you can't get your target asset allocation perfect right off the bat. The most important step is to actually get started investing. If you pay yourself first (see Get in the game) and make investing a habit, you will be able to fund your future. Make it automatic After you've set up your investment account, it's time to remove the human element from the equation to make sure you don't sacrifice 6.5% to the behavior gap (Being on Your Best Behavior) or forget to send your investment check every month.


pages: 263 words: 89,368

925 Ideas to Help You Save Money, Get Out of Debt and Retire a Millionaire So You Can Leave Your Mark on the World by Devin D. Thorpe

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asset allocation, call centre, diversification, estate planning, fixed income, Home mortgage interest deduction, index fund, knowledge economy, money market fund, mortgage tax deduction, payday loans, random walk, risk tolerance, Skype, Steve Jobs, transaction costs, women in the workforce, zero-sum game

As people age, retirement gets closer and the pain of a major setback in investment returns looms larger so they generally shift the allocation to include more bonds and even a bit of cash. It is prudent for most people to keep a portion of their investments in equities even after retirement because retirement itself can last twenty years or more. There are no absolute rules in asset allocation, but many investors seem to see about two-thirds of a portfolio as a limit for any single asset class. Some investors use asset allocation shifts as a way to “time the market,” that is they shift their asset allocation not based on changes in their own circumstances (like nearing retirement) but they shift as their opinion of the markets changes. This practice will increase the risk in your portfolio because you are adding a new variable to the equation. You’ve now added your economic and financial forecasting skills to what is already a complex equation.

Most discount brokers allow you to invest even small amounts in certain mutual funds with no transaction fees. Note that all of the benefits of dollar cost averaging are overwhelmed by brokerage commissions or mutual fund loads. Avoid them. See how easy that was. Dollar cost averaging is something you’re probably already getting the benefit of and now can fully understand. What Is Asset Allocation And How Do I Do It? Asset allocation is the practice of strategically balancing a portfolio among several asset classes. There are three classes of assets that typical families should include in their investments: stocks or equities, bonds and cash. When you finish reading this short article, you’ll know all you need to know to properly balance your portfolio. First, some definitions: Equities: This is a Wall Street word for stocks, referring to their name in the financial statements.

There is plenty of evidence that the Chairman of the Federal Reserve has difficulty forecasting economic results and he can influence them more than anyone. Chances are, you’ll do even worse and risk making your allocation shifts at the wrong times, causing losses you wouldn’t otherwise experience. As you go through life, you can and should slowly adjust your asset allocation. This can often be accomplished simply by investing new dollars in the asset class you’d like to grow. Over time, this should have the effect of reducing the percentage of your portfolio invested in other assets. In this way, you never need to sell assets just to shift your allocation. Thoughtful adjustments to your asset allocation will better prepare you for retirement. What Is A Money Market Fund And How Do I Use One? Learning about money market funds and how to use them in your investing programs can help you make better investment decisions, both protecting your assets and allowing you to earn more in the long run.


pages: 236 words: 77,735

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

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affirmative action, asset allocation, backtesting, barriers to entry, Bernie Madoff, Bretton Woods, 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, too big to fail, trade route, Vanguard fund, walking around money

The fear of making a wrong move or losing money playing a game of picking stocks was a turnoff that needed a solution. This chapter is all about the way Wall Street took some academic ideas and twisted them to sell people securities. Not only that, the very concept of diversification and asset allocation was turned into a sales pitch that after 1987 started to develop cracks in its foundation. A new take on risk—or perhaps the proper one in the first place—is outlined so you can control it. Today’s Outrage: Pie Town It makes me sick to see pie charts and asset allocation pimped out to the average investor. What makes it worse is when I ask the average investor why they have a particular allocation, and they clearly don’t know how it was selected for them. Sure, they will say they told the broker they want to be conservative, or grow the money, or my personal favorite, “make as much as you can without loss.”

Most people ask the wrong questions either out of a lack of understanding of the game or because Wall Street, like a hypnotist, is suggesting the question. This book is written to unravel and illuminate those questions. I get to the bottom of why it’s necessary for Wall Street to have a strategy for every investor, a market for every man, and a philosophy to suit any temperament. If you are a buy and hold investor and are disillusioned by the meltdown, or if you found your asset allocation pie chart to be dubious at best, keep reading. I show you where those concepts came from, why they work or don’t work, and let you be the judge. The very first company that ever floated stock in 1602 was a shaky operation that paid its dividend half in cash and half in spice. Not exactly awe inspiring. That is the start of the rigged system. You only need to make one decision right here and right now.

I look at two different companies, the very first was publicly traded, and one of the best performing of the last 40 years. You would think the incredible returns would prove a buy-and-hold approach. Hindsight identifies a needle in a haystack. But it doesn’t help you today going forward. Buy and hold is a phrase that has very little actual meaning and doesn’t describe any type of investment philosophy as much as a dogma or sales pitch. Even worse, as we enter the modern age of the asset-allocation pie chart, we realize risk has been understated and the very nature of illustration has been misrepresented. Many salespeople in my industry find these ideas dangerous. Why? Essentially, I indict their intellectual credibility and expose their deficiencies. By the end of this section you’ll have a clear idea of how to move forward without the baggage that you and Wall Street have saddled each other with.


pages: 416 words: 118,592

A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing by Burton G. Malkiel

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3Com Palm IPO, accounting loophole / creative accounting, Albert Einstein, asset allocation, asset-backed security, backtesting, beat the dealer, Bernie Madoff, BRICs, capital asset pricing model, compound rate of return, correlation coefficient, Credit Default Swap, Daniel Kahneman / Amos Tversky, diversification, diversified portfolio, Edward Thorp, Elliott wave, Eugene Fama: efficient market hypothesis, experimental subject, feminist movement, financial innovation, fixed income, framing effect, hindsight bias, Home mortgage interest deduction, index fund, invisible hand, Isaac Newton, Long Term Capital Management, loss aversion, margin call, market bubble, money market fund, mortgage tax deduction, new economy, Own Your Own Home, passive investing, Paul Samuelson, pets.com, Ponzi scheme, price stability, profit maximization, publish or perish, purchasing power parity, RAND corporation, random walk, Richard Thaler, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, short selling, Silicon Valley, South Sea Bubble, survivorship bias, The Myth of the Rational Market, the rule of 72, The Wisdom of Crowds, transaction costs, Vanguard fund, zero-coupon bond

Less than 10 percent of investment success is determined by the specific stocks or mutual funds that an individual chooses. In this chapter, I will show you that whatever your aversion to risk—whatever your position on the eat-well, sleep-well scale—your age, income from employment, and specific responsibilities in life go a long way toward helping you determine the mix of assets in your portfolio. FIVE ASSET-ALLOCATION PRINCIPLES Before we can determine a rational basis for making asset-allocation decisions, certain principles must be kept firmly in mind. We’ve covered some of them implicitly in earlier chapters, but treating them explicitly here should prove very helpful. The key principles are: History shows that risk and return are related. The risk of investing in common stocks and bonds depends on the length of time the investments are held.

How did you feel when the market fell by almost 50 percent in 2008? If you panicked and became physically ill because a large proportion of your assets was invested in common stocks, then clearly you should pare down the stock portion of your portfolio. Thus, subjective considerations also play a major role in the asset allocations you can accept, and you may legitimately stray from those recommended here depending on your aversion to risk. 3. Persistent Saving in Regular Amounts, No Matter How Small, Pays Off One final preliminary before presenting the asset-allocation guide. What do you do if right now you have no assets to allocate? So many people of limited means believe that it is impossible to build up a sizable nest egg. Accumulating meaningful amounts of retirement savings often seems out of reach. Don’t despair. The fact is that a program of regular saving each week—persistently followed, as through a payroll savings or 401(k) retirement plan—can in time produce substantial sums of money.

THE LIFE-CYCLE INVESTMENT GUIDE The charts below present a summary of the life-cycle investment guide. In the Talmud, Rabbi Isaac said that one should always divide one’s wealth into three parts: a third in land, a third in merchandise (business), and a third ready at hand (in liquid form). Such an asset allocation is hardly unreasonable, but we can improve on this ancient advice because we have more refined instruments and a greater appreciation of the considerations that make different asset allocations appropriate for different people. The general ideas behind the recommendations have been spelled out in detail above. For those in their twenties, a very aggressive investment portfolio is recommended. At this age, there is lots of time to ride out the peaks and valleys of investment cycles, and you have a lifetime of earnings from employment ahead of you.


pages: 443 words: 51,804

Handbook of Modeling High-Frequency Data in Finance by Frederi G. Viens, Maria C. Mariani, Ionut Florescu

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algorithmic trading, asset allocation, automated trading system, backtesting, Black-Scholes formula, Brownian motion, business process, continuous integration, corporate governance, discrete time, distributed generation, fixed income, Flash crash, housing crisis, implied volatility, incomplete markets, linear programming, mandelbrot fractal, market friction, market microstructure, martingale, Menlo Park, p-value, pattern recognition, performance metric, principal–agent problem, random walk, risk tolerance, risk/return, short selling, statistical model, stochastic process, stochastic volatility, transaction costs, value at risk, volatility smile, Wiener process

Heteroskedasticity Robust Standard Errors are Listed in Parentheses 286 CHAPTER 10 Multivariate Volatility Estimation by Fourier Methods 10.6 Application: Asset Allocation In this section, we consider a different approach to the comparison of covariance estimators with high frequency data, in the context of a relevant economic criterion, developed in Mancino and Sanfelici (2011b). We consider the gains offered by the Fourier estimator over other covariance measures from the perspective of an asset-allocation decision problem, following the approach of Fleming et al. (2001, 2003), Engle and Colacito (2006), Bandi et al. (2008), and De Pooter et al. (2008), who study the impact of volatility timing versus unconditional mean–variance efficient static asset-allocation strategies and of selecting the appropriate sampling frequency or choosing between different bias and variance reduction techniques for the realized covariance matrices.

Proceedings of the IEEE International conference on computational intelligence for financial engineering, Hong Kong, March 20–23, 2003. Hong Kong: IEEE; 2003. p 355–362. Beaver W. Financial ratios as predictors of failure. J Account Res 1966;4:71–111. Berle A, Means G. The modern corporation and private property. New York: Harcourt; 1932. Black F, Litterman R. Asset allocation: combining investor views with market equilibrium. Fixed income research. Goldman Sachs & Co., New York; 1990. Black F, Litterman R. Global asset allocation with equities, bonds, and currencies. Fixed income research, Goldman Sachs & Co., New York; 1991. Bornholdt S. Expectation bubbles in a spin model of markets: intermittency from frustration across scales. Int J Mod Phys C 2001;12:667–674. Breiman L. Statistical modeling: the two cultures. Stat Sci 2001;16:199–231.

We show that the Fourier estimator outperforms the realized volatility/covariance estimator to a significant extent, in particular for high frequency observations and when the noise component is relevant; in general, it has a better performance even in comparison to the methods specifically designed to handle market microstructure contaminations. Finally, in Section 10.6, we consider the gains offered by the Fourier estimator over other covariance measures from the perspective of an asset-allocation decision problem, following the approach of Fleming et al. (2001), who study the impact of volatility timing versus unconditional mean–variance efficient static asset-allocation strategies and of selecting the appropriate sampling frequency or choosing between different bias and variance reduction techniques for the realized covariance matrices. In particular, we show that the Fourier estimator carefully extracts information from noisy high frequency asset price data for the purpose of realized variance/covariance estimation and allows for nonnegligible utility gains in portfolio management. 246 CHAPTER 10 Multivariate Volatility Estimation by Fourier Methods 10.2 Fourier Estimator of Multivariate Spot Volatility Suppose that the prices of n assets p(t) = (p1 (t), . . . , pn (t)) are observed at a continuous time, whose evolutions are continuous semimartingales satisfying the following Itô stochastic differential equations dpj (t) = d j σi (t)dW i + bj (t) dt, j = 1, . . . , n, (10.1) i=1 where W = (W 1 , . . . , W d ) are independent Brownian motions on a filtered probability space satisfying the usual conditions and σ∗∗ and b∗ are adapted random processes satisfying (H) E T (b (t)) dt < ∞, i 2 E 0 0 T j (σi (t))4 dt <∞ i = 1, . . . , d, j = 1, . . . , n.


pages: 1,088 words: 228,743

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

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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, 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, 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, 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, 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

Striving to build a bridge between academic and practitioner worlds, this book focuses on intuition and contains almost no equations and only very basic statistics [7]. For many academics the book will thus seem insufficiently rigorous, while for some practitioners it may be too intense. My target audience, unsurprisingly, is in the middle: experienced professional investors still hungry to learn, including top-down asset allocators and fund trustees—as well as advanced finance students in CFA or MBA programs. Outline When designing the book’s structure, I needed to find a compromise between discussing broad issues common to many asset classes and providing evidence on specific asset classes, strategies, or factors. I decided to do both, while trying to avoid repetition. Parts I and III are broad while Part II focuses on specific cases.

Chapter 24 will give a slightly broader overview on forecasting models and dynamic trading strategies. Figure 2.7 shows proxies of ex ante real yields of major U.S. asset classes over a very long historical period. Real yields are calculated as explained in Appendix B. Clearly, these yields vary a lot over time. If we take them at face value, the relative attractiveness of different asset classes varies drastically over time, suggesting that value-oriented market timing or tactical asset allocation strategies can be profitable. These indicators have their own shortcomings, but empirical evidence indicates that they do have some ability to forecast long-term asset returns. Figure 2.7. Forward-looking real yields of U.S. equities, corporate bonds, Treasuries, and housing, 1900–2009. Sources: Bloomberg, Robert Shiller’s website, Moody’s, Ibbotson Associates (Morningstar), Federal Reserve Board, Davis–Lehnert–Martin (2008)/Lincoln Institute of Land Policy, National Bureau of Economic Research.

This story can explain the low equity market valuations in the 1970s and high valuations in the 1990s. It is unlikely that money illusion was complete, in the sense of all investors making the mistake described above; but an insufficient adjustment for inflation effects is enough to distort market pricing, given the extreme sensitivity of equity prices to their discount rates. The continuing popularity of the “Fed model”—an asset allocation analysis comparing (real) earnings yields with (nominal) bond yields—is suggestive of money illusion. The money illusion anomaly at the market level is non-diversifiable and slow moving, making it particularly unattractive to arbitrage. Related anomalies have been observed in equity, bond, and housing markets. However, simple money illusion stories are not sufficient to explain all asset price histories: equity market valuations were cheap both in the deflationary 1930s and the inflationary 1970s, while housing markets boomed amidst high inflation in the 1970s and amidst low inflation in the 2000s. 6.3.2 Cross-sectional trading opportunities and micro-inefficiency If the bubble story above says that shifting investor sentiment over time creates periods of overvaluation and undervaluation in the aggregate equity market level that a contrarian market-timer can exploit, then varying investor sentiment across individual stocks creates cross-sectional opportunities that a contrarian stock-picker can exploit.


pages: 162 words: 50,108

The Little Book of Hedge Funds by Anthony Scaramucci

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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, the new new thing, too big to fail, transaction costs, Vanguard fund, Y2K, Yogi Berra, zero-sum game

True, they may appear riskier than traditional vanilla mutual funds, but many of them are actually less risky and provide better returns. That being said, hedge funds are not for everyone nor are they a substitute for other investment vehicles. For many people, mutual funds—with a swirl of alternative asset or hedge fund exposure—are probably the best option. It isn’t a one-size-fits-all sort of approach; however, a portfolio of hedge fund portfolios can be sleeved into most investors’ tactical asset allocation. A word of warning: Before anyone invests in this industry, they must heed this surgeon general’s warning—investing without proper due diligence or proper personal risk assessment can be bad for your mental and financial health. Do your homework. Be prepared. Have a proper screen. Research. Research. Research. So, let’s find out just who can invest in these enigmatic and stealth investment vehicles and how every dentist in the United States can get in the game.

Maybe years from now regulators will require an IQ test or a note from a psychiatrist or possibly a rectal exam (Lord knows many of us have our brains down there!), but until then read the partnership documents carefully and seek out professional advice before investing. Both sophisticated investors and unsophisticated ones have a need for protection against risk. With careful analysis and the right due diligence and asset allocation one can achieve this goal by using hedge funds as an investment tool. The Institutional Invasion In early 2000, hedge funds were in trouble. Julian Robertson’s Tiger Fund had been overtaken by “mouse clicks and momentum.” George Soros’ Quantum Fund was down 21 percent and Stan Druckenmiller was leaving the fund after a dozen years; they, too, would be closing the curtain on their original proposition.

Discussed in a paper entitled “Portfolio Selection,” this theory postulated that it was not enough to simply maximize returns but one must maximize risk-adjusted returns, whereby returns would be based upon a given level of inherent risk. The key to his theory was that the risk of a portfolio is dependent upon the relationship among its securities. In other words, if you picked the right securities or had the right asset allocation you could get out on the efficient frontier and actually find a scenario where you earned more reward yet took less risk. Back in the 1950s, the problem with this approach was that it was not easy to implement—there simply wasn’t enough time or resources to calculate the correlations between thousands of stocks—or (at that time) just 25! And so, picking up where Markowitz left off, William Sharpe put a spin on this theory and simplified it by calculating a single correlation between each stock and the market index (rather than calculating multiple relationships).


pages: 300 words: 77,787

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

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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

Think of everything and think out of the box to compile your lists. Of course it would be great if the performance of your various assets in no way correlated, but unfortunately that is not very realistic. Most things link to the economy somehow. If we were presented with perfect data sets regarding the values, risks and correlations of an investor’s other assets we would be able to do some sort of scientific optimisation of asset allocation. That, however, is almost impossible. The idea of taking assets, including intangible ones, and optimising allocations based on them probably sounds like nonsense to most people. But while we don’t have the data or desire to do these calculations in a scientific way it’s still worth nurturing your gut instinct about how this all fits together. A simple way to start thinking about the non-investment assets is asking yourself if there is something you really don’t want to happen, and go from there.

So if you need to borrow money and can do it through your property then that may be the cheapest way. 2 Although the quoted property investment companies that are represented in the index trackers only represent a small proportion of the value of the world’s total property that is also true of many other industries. Also, if this small quoted representation of property holding suggested that those quoted were extra attractive we would trust the market to have this reflected in the share price relative to other securities. 3 According to Richard Ferri’s excellent book All About Asset Allocation (McGraw-Hill Professional, 2010) about two-thirds of the total value of commercial property in the US is owned by corporations, many of which you are already invested in through the general equity market index. 4 There is obviously a millennia-long price history of commodities, but to my knowledge not in an aggregated index that can be replicated in financial products like ETFs or mutual funds. 5 The total return index includes interest on the ‘free’ cash when investing in futures.

The right product for you is really an individual choice dependent partly on your tax and currency situation. But the key facts are the same. Buy as broad an index tracker as you can and as cheaply as you can. If you do that, you are doing pretty well. 1 At the time of writing, in the UK the only way to buy the Vanguard funds below £100,000 is through Alliance Trust. Vanguard has been making noises about introducing easier and more direct options. 2 See The Intelligent Asset Allocator: How to Build Your Portfolio to Maximize Returns and Minimize Risk by William Bernstein (American Media International LLC, 2004). part four Other things to think about chapter 15 * * * Pension and insurance For many individuals their investing lives are dominated less by issues relating to their rational portfolio, but rather by the options and choices with regard to pensions, life annuities and related products.


pages: 670 words: 194,502

The Intelligent Investor (Collins Business Essentials) by Benjamin Graham, Jason Zweig

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3Com Palm IPO, accounting loophole / creative accounting, air freight, Andrei Shleifer, asset allocation, buy low sell high, capital asset pricing model, corporate governance, corporate raider, Daniel Kahneman / Amos Tversky, diversified portfolio, Eugene Fama: efficient market hypothesis, George Santayana, hiring and firing, index fund, intangible asset, Isaac Newton, Long Term Capital Management, market bubble, merger arbitrage, money market fund, new economy, passive investing, price stability, Ralph Waldo Emerson, Richard Thaler, risk tolerance, Robert Shiller, Robert Shiller, Ronald Reagan, shareholder value, sharing economy, short selling, Silicon Valley, South Sea Bubble, Steve Jobs, survivorship bias, the market place, the rule of 72, transaction costs, tulip mania, VA Linux, Vanguard fund, Y2K, Yogi Berra

Applied Materials Applied Micro Devices appreciation arbitrages Archer-Daniels-Midland Ariba Aristotle Arnott, Robert artwork “as if” statements. See pro forma statements Asness, Clifford asset allocation: and advice for investors; and aggressive investors; and defensive investors; plan of; and history and forecasting of stock market; and inflation; and institutional investors; and investments vs. speculation; and market fluctuations; tactical. See also diversification asset backing. See book value assets: elephantiasis of; and per-share earnings; and security analysis; and stock selection for aggressive investors; and stock selection for defensive investors. See also asset allocation; specific company Association for Investment Management and Research AT&T Corp. See also American Telephone & Telegraph Atchison, Topeka & Santa Fe Atlantic City Electric Co.

All too many investors thought they were diversified in the late 1990s because they owned 39 “different” Internet stocks, or seven “different” U.S. growth-stock funds. But that’s like thinking that an all-soprano chorus can handle singing “Old Man River” better than a soprano soloist can. No matter how many sopranos you add, that chorus will never be able to nail all those low notes until some baritones join the group. Likewise, if all your holdings go up and down together, you lack the investing harmony that true diversification brings. A professional “asset-allocation” plan can help. Major changes. If you’ve become self-employed and need to set up a retirement plan, your aging parents don’t have their finances in order, or college for your kids looks unaffordable, an adviser can not only provide peace of mind but help you make genuine improvements in the quality of your life. What’s more, a qualified professional can ensure that you benefit from and comply with the staggering complexity of the tax laws and retirement rules.

“options strategy” “It’s a no-brainer.” “You can’t afford not to own it.” “We can beat the market.” “You’ll be sorry if you don’t…” “exclusive” “You should focus on performance, not fees.” “Don’t you want to be rich?” “can’t lose” “The upside is huge.” “There’s no downside.” “I’m putting my mother in it.” “Trust me.” “commodities trading” “monthly returns” “active asset-allocation strategy” “We can cap your downside.” “No one else knows how to do this.” Getting to Know You A leading financial-planning newsletter recently canvassed dozens of advisers to get their thoughts on how you should go about interviewing them.4 In screening an adviser, your goals should be to: determine whether he or she cares about helping clients, or just goes through the motions establish whether he or she understands the fundamental principles of investing as they are outlined in this book assess whether he or she is sufficiently educated, trained, and experienced to help you.

Trade Your Way to Financial Freedom by van K. Tharp

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asset allocation, commodity trading advisor, compound rate of return, computer age, Elliott wave, high net worth, margin call, market fundamentalism, pattern recognition, prediction markets, random walk, risk tolerance, short selling, statistical model, transaction costs

You have a 0.5 percent chance (3 standard deviations) of a 30 percent drawdown These results are excellent, but if you believe you will be in serious trouble if you lose 20 percent or more, Kaufman suggests that you only trade a portion of the funds allocated to you. Kaufman also talks about asset allocation,s which he defines as “the process of distributing investment funds into one or more markets or vehicles to create an investment profile with the most desirable return/risk ratio.” Asset allocation may simply amount to trading half of vour capital with one active investment (i.e., a stock portfolio) while the rest of your capital is in short-term yieldbearing instruments such as government bonds. On the other hand, asset allocation may involve combining many investment vehicles in a dynamic approach-such as actively trading stocks, commodities, and the forex market. It’s clear from Kaufman’s discussion, although he doesn’t state it directly, that he is used to using the first position-sizing model-the one unit per so much capital.

However, Kaufman is making the assumption that returns are normally distributed. Since market prices are not, returns may not be either. 8. Asset allocation was shown by Brinson, Singer, and Beebower (“Determinants of Portfolio Performance 11: An Update.” Financial Annlysk Journal, 1991,47,40-49) to account for 91.5 percent of the variability of returns of 82 pension plans over a lo-year period. Stock selection and other types of decision making had very little influence on the returns. Brinson et al.‘s definition of “asset allocation” was really position sizing-since it just indicated what percentage of the capital was in stocks, bonds, and cash. Professionals then became very excited about asset allocation, but its meaning was changed to reflect the lotto bias-it now seems to mean “selecting the right assets.” 9. In my opinion, this assumption allows a lot of people to trade and makes it seem as if there is little risk involved.

Raleigh, NC: International Institute of Trading Mastery, 1947. Call 1. 919-362-5591 for more information. This is our original systems seminar, which is great information for all traders and investors. Vine, Ralph. Portfolio Management Formulas: Mnthenmticai Trading Methods for the Futures, Options, and StockMarkets. New York: Wiley, 1990. Difficult reading, but most professionals should tackle it. Vine, Ralph. The Nm Money Managment: A Frnmrwork for Asset Allocation. New York: Wiley, 1995. An improvement from Portfolio Managmenf Formulas and again a book that most professionals in the field of investing and trading should read. Wilder, J. Wells, Jr. New Concepts in Technical Trading. Greensboro, NC: Trend Research, 1978. One of the classics of trading and a must read. APPENDIX II Key Terms Defined Adaptive Moving Average A moving average that is either quick, or slow, to signal a market entry depending upon the efficiency of the move in the market.


pages: 354 words: 26,550

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

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algorithmic trading, asset allocation, asset-backed security, automated trading system, backtesting, Black Swan, Brownian motion, business process, 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

—Alternative RAPMs for Alternative Investments.” Journal of Investment Management 2 (4), 106–129. Sharpe, William F., 1964. “Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk.” Journal of Finance 19, 425–442. Sharpe, William F., 1966. “Mutual Fund Performance.” Journal of Business 39 (1), 119–138. Sharpe, William F., 1992. “Asset Allocation: Management Style and Performance Measurement.” Journal of Portfolio Management, Winter 7–19. Sharpe, William F., 2007. “Expected Utility Asset Allocation.” Financial Analysts Journal 63 (September/October), 18–30. References 321 Simpson, Marc W. and Sanjay Ramchander, 2004. “An Examination of the Impact of Macroeconomic News on the Spot and Futures Treasury Markets.” Journal of Futures Markets 24, 453–478. Simpson, Marc W., Sanjay Ramchander and James R. Webb, 2007.

Conversely, the lower the market value of the portfolio, the higher the proportion of the portfolio that is held in cash or in nearly risk-free fixed-income securities. What Proportion of the Portfolio Should Be Invested into Which Trading Strategy? After the performance of individual securities and trading strategies has been assessed and the best performers identified, the composition of the master portfolio is determined from the best-performing strategies. This step of the process is known as asset allocation and involves determining the relative weights of strategies within the master portfolio. The easiest approach to portfolio optimization is to create an equally weighted portfolio of the best-performing strategies. Although the equally weighted framework diversifies the risk of the overall portfolio, it may not diversify the risk as well as a thorough portfolio optimization process. As the number of securities in the portfolio increases, however, determining the optimal weights for each security becomes increasingly complex and time-consuming—a real challenge in the high-frequency environment.

“Reports of Beta’s Death Are Premature: Evidence from the UK.” Journal of Banking and Finance 22, 1207– 1229. Cochrane, J., 2005. Asset Pricing (2nd edition). Princeton, NJ: Princeton University Press. Cohen, K., S. Maier, R. Schwartz and D. Whitcomb, 1981. “Transaction Costs, Order Placement Strategy, and Existence of the Bid-Ask Spread.” Journal of Political Economy 89, 287–305. Colacito, Riccardo and Robert Engle, 2004. “Multiperiod Asset Allocation with Dynamic Volatilities.” Working paper. Coleman, M., 1990. “Cointegration-Based Tests of Daily Foreign Exchange Market Efficiency.” Economic Letters 32, 53–59. Connolly, Robert A. and Chris Stivers, 2005. “Macroeconomic News, Stock Turnover, and Volatility Clustering in Daily Stock Returns.” Journal of Financial Research 28, 235–259. Constantinides, George, 1986. “Capital Market Equilibrium with Transaction Costs.”


pages: 416 words: 39,022

Asset and Risk Management: Risk Oriented Finance by Louis Esch, Robert Kieffer, Thierry Lopez

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asset allocation, Brownian motion, business continuity plan, business process, capital asset pricing model, computer age, corporate governance, discrete time, diversified portfolio, fixed income, implied volatility, index fund, interest rate derivative, iterative process, P = NP, p-value, random walk, risk/return, shareholder value, statistical model, stochastic process, transaction costs, value at risk, Wiener process, yield curve, zero-coupon bond

To close this fourth part, we will see how the APT model described in Section 3.3.2 allows investment funds to be analysed in behavioural terms. Asset management Fund management Portfolio management • Asset allocation & market timing • Stock picking • Currency allocation • Portfolio risk management • Fund risk management Asset and risk management • • • • • Stop loss Credit equivalent VBP VaR MRO Risk management Figure P1 Asset and risk management 1 In fact, the statistical distribution of an equity is leptokurtic but becomes normal over a sufficiently long period. 9 Portfolio Risk Management1 9.1 GENERAL PRINCIPLES This involves application of the following: • To portfolios managed traditionally, that is, using: — asset allocation with a greater or lesser risk profile (including, implicitly, market timing); — a choice of specific securities within the category of equities or options (stock picking); — currency allocation. • To particularly high-risk portfolios (said to have a ‘high leverage effect’) falling clearly outside the scope of traditional management (the most frequent case), a fivefold risk management method that allows: — daily monitoring by the client (and intraday monitoring if market conditions require) of the market risks to which he or she is exposed given the composition of his or her portfolio. — monitoring of equal regularity by the banker (or wealth manager where applicable) of the client positions for which he or she is by nature the only person responsible.

Table 10.9 Classification of assets Classification Equity 5 Equity 2 Equity 3 Equity 1 Equity 4 Bond 2 Bond 1 Table 10.10 1.238051233 1.180947722 0.921654797 0.764163854 0.620600304 0.614979773 0.19802287 Composition of portfolio Classification Equity 1 Equity 2 Equity 3 Equity 4 Equity 5 Bond 1 Bond 2 0.070416113 0.114350746 0.068504735 0.036360401 0.146993068 0.041847479 0.521527457 Table 10.11 VaR premiums on the various assets 35 Classification VaR premium Equity 1 Equity 2 Equity 3 Equity 4 Equity 5 Bond 1 Bond 2 Portfolio 0.031922988 0.028453485 0.024136102 0.023352806 0.030366115 0.000722099 0.001690335 0.0576611529 See the CD-ROM attached to this book, ‘Global optimisation of VaR premium.xls’. Optimising the Global Portfolio via VaR 283 Finally, the major advantage of this method is that it allows a portfolio to be optimised in terms of asset allocation as well as stock picking, which is not the case with the pooling methods. In pooling, the combinations of benchmarks do not take account of the correlation between these and still less take account of the correlation between each asset making up the benchmarks. This is the great advantage of the method, as asset allocation accounts for the greater part of a portfolio manager’s work. 11 Institutional Management: APT Applied to Investment Funds The APT1 model described in Section 3.3.2 allows the behaviour of investment funds to be analysed in seven points. 11.1 ABSOLUTE GLOBAL RISK Normal volatility (the ‘standard deviation’ of statisticians) is a measurement of the impact of all market conditions observed during a year on the behaviour of an asset.

A fully efficient market can be beaten only temporarily and by chance: in the long term, the return cannot exceed the market return. Active management therefore suggests that the market is fully efficient. 48 This type of situation is known in price theory as a zero total game. Refer for example to Binmore K., Jeux et théorie des jeux, De Boeck & Larcier, 1999. 104 Asset and Risk Management Two main principles allow the target set to be achieved. 1) Asset allocation, which evolves over time and is also known as market timing, consists of putting together a portfolio consisting partly of the market portfolio or an index portfolio and partly of a risk-free asset (or one that is significantly less risk than equities, such as a bond). The respective proportions of these two components are then changed as time passes, depending on whether a rise or a fall in the index is anticipated. 2) Stock picking consists of putting together a portfolio of equities by choosing the securities considered to be undervalued and likely to produce a return higher than the market return in the near or more distant future (market reaction).

Investment: A History by Norton Reamer, Jesse Downing

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activist fund / activist shareholder / activist investor, Albert Einstein, algorithmic trading, asset allocation, backtesting, banking crisis, Berlin Wall, Bernie Madoff, break the buck, Brownian motion, buttonwood tree, California gold rush, capital asset pricing model, Carmen Reinhart, carried interest, colonial rule, credit crunch, Credit Default Swap, Daniel Kahneman / Amos Tversky, debt deflation, discounted cash flows, diversified portfolio, equity premium, estate planning, Eugene Fama: efficient market hypothesis, Fall of the Berlin Wall, family office, Fellow of the Royal Society, financial innovation, fixed income, Gordon Gekko, Henri Poincaré, high net worth, index fund, information asymmetry, interest rate swap, invention of the telegraph, James Hargreaves, James Watt: steam engine, joint-stock company, Kenneth Rogoff, labor-force participation, land tenure, London Interbank Offered Rate, Long Term Capital Management, loss aversion, Louis Bachelier, margin call, means of production, Menlo Park, merger arbitrage, money market fund, moral hazard, mortgage debt, Myron Scholes, negative equity, Network effects, new economy, Nick Leeson, Own Your Own Home, Paul Samuelson, pension reform, Ponzi scheme, price mechanism, principal–agent problem, profit maximization, quantitative easing, RAND corporation, random walk, Renaissance Technologies, Richard Thaler, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, Sand Hill Road, Sharpe ratio, short selling, Silicon Valley, South Sea Bubble, sovereign wealth fund, spinning jenny, statistical arbitrage, survivorship bias, technology bubble, The Wealth of Nations by Adam Smith, time value of money, too big to fail, transaction costs, underbanked, Vanguard fund, working poor, yield curve

One study draws data from a combination of two databases (the TASS and the HFR) and performs an analysis of funds of funds over an eight-year period. The study concludes that, in fact, funds of funds do succeed, in aggregate, in adding value net of fees. Equally interesting, however, is the performance attribution: the funds of funds are successful because of sound strategic asset allocation rather than tactical asset allocation. In fact, the study finds that on average, the tactical asset allocation seems to add zero or negative value in most years, though part of this may be due to the underlying managers’ liquidity constraints (a fund of funds cannot reallocate funds immediately, since the funds are often at the whim of redemption windows).31 Illiquidity of the Vehicle Hedge funds are less liquid than many other investment vehicles available in the market.

UMIFA specified that assets should be deployed across asset classes (diversification) while UPMIFA updated those codes by New Clients and New Investments 125 additionally stipulating that investments must be executed in accordance with a prudent person standard and “in good faith.”10 Diversification is continuing to be a highly effective investment strategy for endowments. By way of example, as of June 2005, the average educational endowment held 53 percent in domestic equity, 23 percent in domestic fixed income, and 5 percent in cash.11 Six years later, by June 2011, the average educational endowment’s asset allocation was 16 percent in domestic equities, 10 percent in fixed income, 17 percent in international equities, 53 percent in alternative strategies, and 4 percent in cash or other general assets.12 In short, endowment diversification is following the current investment trends by becoming more international, as well as taking advantage of more niche strategies. Foundations The foundation, in its modern form, dates back to the turn of the twentieth century, when many industrialists found themselves with enormous wealth they could funnel toward the improvement of society.

This creates a difficult problem of finding an investment adviser willing and able to take on such a responsibility at what is often an inadequate level of compensation. It is on this conundrum that the frequently heard advice for the average individual client to limit himself or herself to low-cost index products rests. Consequently, there is, sadly, no alternative to individuals’ accepting some level of responsibility for their own asset allocation—a daunting task for all but a very few. For those still early in accumulation careers, a balanced approach, coupled with courageous dollar cost averaging appears to be required. But undertaking and maintaining such a strategy requires nerves of steel at certain times. INVESTMENT AND SOCIAL CHANGE Given that the powerful project of democratization is well underway, our expectations of it can be extended further.


pages: 398 words: 86,855

Bad Data Handbook by Q. Ethan McCallum

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Amazon Mechanical Turk, asset allocation, barriers to entry, Benoit Mandelbrot, business intelligence, cellular automata, chief data officer, Chuck Templeton: OpenTable, cloud computing, cognitive dissonance, combinatorial explosion, commoditize, conceptual framework, database schema, en.wikipedia.org, Firefox, Flash crash, Gini coefficient, illegal immigration, iterative process, labor-force participation, loose coupling, natural language processing, Netflix Prize, quantitative trading / quantitative finance, recommendation engine, selection bias, sentiment analysis, statistical model, supply-chain management, survivorship bias, text mining, too big to fail, web application

Let’s take a simple case, an asset allocated to two cost centers. An SQL query to retrieve our allocations is: select * from assets inner join assets_cost_centers on assets.asset_id = assets_cost_centers.asset_id inner join cost_centers on assets_cost_centers.cost_center_id = cost_centers.cost_center_id; Two sample rows might look like the following: asset_idnamedescriptionasset_idcost_center_ideffective_datepercentagecost_center_idnamedescription 1 web server the box… 1 1 2012-01-01… 0.20000 1 IT 101 web services 1 web server the box… 1 2 2012-01-01… 0.80000 2 SAAS 202 software services The percentage attribute in each row gives us the ratio of the asset’s cost that the cost center will be charged. In general, the total asset allocation to the cost center in each row is the product of the allocation percentages on the relationships in between the asset and the cost center.

This is fairly trivial for a direct allocation, but let’s look at the query for asset to service, service to product, product to department, and department to cost center: select * from assets inner join assets_services on assets.asset_id = assets_services.asset_id inner join services on assets_services.service_id = services.service_id inner join services_products on services.service_id = services_products.service_id inner join products on services_products.product_id = products.product_id inner join products_departments on products.product_id = products_departments.product_id inner join departments on products_departments.department_id = departments.department_id inner join departments_cost_centers on departments.department_id = departments_cost_centers.department_id inner join cost_centers on departments_cost_centers.cost_center_id = cost_centers.cost_center_id One of the resulting rows would look like: assetpercentageservicepercentageproductpercentagedepartmentpercentagecost_center file server 0.10000 Data Science S… 0.40000 Search Engine 0.7000 R&D 0.25000 SAAS 201 Our allocation percentage here is now the product of the allocation percentages in between the asset and the cost center. For this row, we have A server with a $3,000 monthly charge would, therefore, cost the SAAS 202 cost center $21 per month. These are only the two corner cases, representing the shortest and the longest queries. We’ll also need queries for all the cases in between if we continue with this design to cover assets allocated to departments and products allocated to cost centers. Each new level of the query adds to a combinatorial explosion and begs many questions about the design. What happens if we change the allocation rules? What if a product can be allocated directly to a cost center instead of passing through a department? Are the queries efficient as the amount of data in the system increases? Is the system testable?

Benoît Mandelbrot[62] In just three iterations of this algorithm, we can create a famous shape known as the Koch snowflake.[63] Not so different than what just happened with our relational schema, is it? Our entities play the role of the “straight interval,” and the associative many-to-many entities act as the complexity generators. The Hidden Network Emerges Let’s step back. If we were to just step up to a whiteboard and draw out what we were trying to accomplish with the asset allocations for our servers, our sketch might look something like Figure 13-2. Figure 13-2. Visual model of what’s being accomplished The visual model makes it easier to see that, for purposes of calculating allocated cost, there really isn’t a great deal of difference among these “types.” At the most fundamental level, there are dots, lines, and text describing both. We can read the first dot and line in this drawing as, “The File Server asset is allocated 10% to the Data Science service.”


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

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 process, butterfly effect, capital asset pricing model, Captain Sullenberger Hudson, Carmen Reinhart, Chance favours the prepared mind, 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, 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, Richard Feynman: Challenger O-ring, risk tolerance, Robert Shiller, Robert Shiller, short selling, sovereign wealth fund, statistical arbitrage, Steven Pinker, stochastic process, survivorship bias, 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

The expected return of an investment is linearly related to its risk (in other words, plotting risk versus expected return on a graph should show a straight line), and is governed by an economic model known as the Capital Asset Pricing Model, or CAPM (more on this later). Principle 3: Portfolio Optimization and Passive Investing. Using statistical estimates derived from Principle 2 and the CAPM, portfolio managers can construct diversified long-only portfolios of fi nancial assets that offer investors attractive risk-adjusted rates of return at low cost. Principle 4: Asset Allocation. Choosing how much to invest in broad asset classes is more important than picking individual securities, so the asset allocation decision is sufficient for managing the risk of an investor’s savings. Principle 5: Stocks for the Long Run. Investors should hold mostly equities for the long run. Principle 1 is straightforward: the only way investors would willingly take on a higher-risk asset is if they’re given an incentive for doing so, and that incentive comes in the form of higher expected return.

There are fancier heuristics that attempt to reduce your risk as you get closer to retirement, like investing a percentage of 100-minus-your-age in stocks and the rest in bonds, so a twenty-yearold will have 80 percent in stocks, while a sixty-five-year-old will only Adaptive Markets in Action • 253 have 35 percent in stocks. The idea is to adjust your asset allocation to suit your risk tolerance and your long-run investment objectives. Principle 5 makes your asset allocation decision even simpler: just hold stocks for the long run. This principle is based on the hugely influential book Stocks for the Long Run, written by the Wharton financial economist Jeremy Siegel.2 First published in 1994, this book is now in its fifth edition, and has become the “buy and hold Bible” of the investment management industry.

Portfolio optimization tools are only useful if the assumptions of stationarity and rationality are good approximations to reality. The notion of passive investing is changing due to technological advances, and risk management should be a higher priority, even for passive index funds. Principle 4A: Asset Allocation. The boundaries between asset classes are becoming blurred, as macro factors and new financial institutions create links and contagion across previously unrelated assets. Managing risk through asset allocation is no longer as effective today as it was during the Great Modulation. Adaptive Markets in Action • 283 Principle 5A: Stocks for the Long Run. Equities do offer attractive returns over the very long run, but few investors can afford to wait it out. Over more realistic investment horizons, the chances of loss are significantly greater, so investors need to be more proactive about managing their risk.


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

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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

Then Bridgewater does that for every single position—the firm has about 100 uncorrelated alpha streams in its alpha portfolio at any given time. Perhaps the most important application of this portfolio engineering has nothing to do with the firm’s Pure Alpha strategy. In 1994, faced with his own portfolio management decisions, Dalio created the “All Weather portfolio”—a passive asset allocation that was designed to take full advantage of diversification. “In the mid-90s I started to accumulate some money that I wanted to use to establish a family trust, and for that trust I wanted the right asset allocation mix,” he recalls. “That’s when I created the All Weather portfolio, which now accounts for virtually all of that family trust money.” In 2001, following the equity market crash, Britt Harris, CIO of the Verizon pension fund, would become Bridgewater’s first institutional client to use All Weather.

Dalio called it “Post-Modern Portfolio Theory (PMPT)” because it built on the concepts of portfolio theory, but went a few steps beyond. Regarding All Weather, Dalio wrote, “I believe that, as this approach is increasingly adopted, it will have a radical beneficial impact on asset allocation that will be of a similar magnitude to that of traditional portfolio theory as it gained acceptance.” Indeed, following the stress test of the 2008 financial crisis when most investor portfolios were down 40 percent into the stock market bottom, an All Weather portfolio was down less than 10 percent. Over its lifetime, it has outperformed the conventional 60/40 stock/bond asset allocation with only half the risk. Seeing the potential for such a strategy, other money managers quickly sought to replicate the passive All Weather approach, and the industry adopted the name “Risk Parity” for such approaches.


pages: 368 words: 32,950

How the City Really Works: The Definitive Guide to Money and Investing in London's Square Mile by Alexander Davidson

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accounting loophole / creative accounting, algorithmic trading, asset allocation, asset-backed security, bank run, banking crisis, barriers to entry, Big bang: deregulation of the City of London, capital asset pricing model, central bank independence, corporate governance, Credit Default Swap, dematerialisation, discounted cash flows, diversified portfolio, double entry bookkeeping, Edward Lloyd's coffeehouse, Elliott wave, Exxon Valdez, forensic accounting, global reserve currency, high net worth, index fund, inflation targeting, intangible asset, interest rate derivative, interest rate swap, John Meriwether, London Interbank Offered Rate, Long Term Capital Management, margin call, market fundamentalism, Nick Leeson, North Sea oil, Northern Rock, pension reform, Piper Alpha, price stability, purchasing power parity, Real Time Gross Settlement, reserve currency, Right to Buy, shareholder value, short selling, The Wealth of Nations by Adam Smith, transaction costs, value at risk, yield curve, zero-coupon bond

Contrary to popular belief, conventional fund managers have far more trading power than the hedge fund managers (see below). They can move prices by their buy and sell decisions, and by accepting or rejecting a bid for a company in which they hold shares, may determine the success of the bid.  156 HOW THE CITY REALLY WORKS ________________________________ Fund managers cannot invest in anything they like, as they are subject to asset allocation and asset eligibility requirements. Some funds invest in large blue chips, others in small companies, some in the UK and others abroad. These boundaries are known as the fund manager’s universe. Some fund managers are top-down, which means that they start with the global macroeconomic view and, within this framework, select individual stocks. Other managers are bottom-up, which means that they focus initially on the stocks, and only then on the broader picture.

Under changes to accounting standards, pension funds have been required to account for future liabilities on a current basis, which means that they must have assets to meet them. As a result of the pressures, some companies have closed schemes or increased contributions, and there has been some shift in investment from equities into bonds. Liability-driven investment (LDI) responds to the need to match the asset allocation of a pension scheme more closely with future liabilities, but it requires a more sophisticated approach than shifting from equities into fixed income, given the payment profiles of funds, coupled with inflation and interest rate risk, according to the IMA. So far, LDI accounts for only 6 per cent of total pension fund assets under management, and is seen by some as only a partial solution. Pension deficits remain an issue.

Myners highlighted the need for greater transparency in how pension funds were used. It found that many pension fund trustees lacked the investment expertise to assess services sold to them by investment consultants and fund managers, and relied on a small number of investment consultants supplying bundled actuarial and investment advice. Myners found that pension funds devoted insufficient resources to asset allocation, and that unclear contractual structures created unnecessary incentives for short termism in investment. He said there was insufficient focus on adding value through shareholder engagement, and that pension fund trustees should voluntarily adopt best-practice principles for investment decision making on a ‘comply or explain’ basis. Only individuals with the right skill and experience should take decisions, he said.


pages: 402 words: 110,972

Nerds on Wall Street: Math, Machines and Wired Markets by David J. Leinweber

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AI winter, algorithmic trading, asset allocation, banking crisis, barriers to entry, Big bang: deregulation of the City of London, butterfly effect, buttonwood tree, buy low sell high, capital asset pricing model, citizen journalism, collateralized debt obligation, corporate governance, Craig Reynolds: boids flock, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Danny Hillis, demand response, disintermediation, distributed generation, diversification, diversified portfolio, Emanuel Derman, en.wikipedia.org, experimental economics, financial innovation, fixed income, Gordon Gekko, implied volatility, index arbitrage, index fund, information retrieval, intangible asset, Internet Archive, John Nash: game theory, Kenneth Arrow, Khan Academy, load shedding, Long Term Capital Management, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, market fragmentation, market microstructure, Mars Rover, Metcalfe’s law, moral hazard, mutually assured destruction, Myron Scholes, natural language processing, negative equity, Network effects, optical character recognition, paper trading, passive investing, pez dispenser, phenotype, prediction markets, quantitative hedge fund, quantitative trading / quantitative finance, QWERTY keyboard, RAND corporation, random walk, Ray Kurzweil, Renaissance Technologies, Richard Stallman, risk tolerance, risk-adjusted returns, risk/return, Robert Metcalfe, Ronald Reagan, Rubik’s Cube, semantic web, Sharpe ratio, short selling, Silicon Valley, Small Order Execution System, smart grid, smart meter, social web, South Sea Bubble, statistical arbitrage, statistical model, Steve Jobs, Steven Levy, Tacoma Narrows Bridge, the scientific method, The Wisdom of Crowds, time value of money, too big to fail, transaction costs, Turing machine, Upton Sinclair, value at risk, Vernor Vinge, yield curve, Yogi Berra, your tax dollars at work

They can also use the results of these adjustments to refine or restructure the process still further. When people do this, we call it “learning.” These AI systems are much more modest than the grand AI ultimate goal of machine sentience. They are typically the extended applications of quantitative techniques, enhanced by machine learning. Artificial learning systems are now being applied in finance and investment. Applications include asset allocation, quantitative equity portfolio management, market making, and currency trading. That was 1995. To hear how some of this turned out, keep reading the next chapter. Notes 1. One of those numerical meteorology problems led to the discovery of deterministic chaos, the strong dependence of a result on what was presumed to be meaninglessly small differences in the inputs. This was popularized as the so-called butterfly effect, A Little AI Goes a Long Way on Wall Str eet 179 since the seemingly insignificant pressure changes caused by a fluttering butterfly, well within the limits of error of barometers used to measure them, could result in wildly different simulated future weather and climate outcomes.

The simplest Basic—Variables fixed in advance AVG1 SBP gene LAG1 AVG2 LAG2 AVG1 BRP gene LAG1 AVG2 LAG2 Snappy Version—Variables and transforms coded VAR ID X FORM AVG1 LAG1 AVG2 LAG2 VAR ID Really Snappy Version—As above, plus variation in algebraic form PRED ID PRED ID OP VAR ID X FORM VAR ID X FORM AVG1 AVG1 LAG1 LAG1 AVG2 AVG2 LAG2 LAG2 Figure 8.4 Chromosomes for Global Tactical Asset Allocation (GTAA) and Tactical Currency Allocation (TCA) Models Perils and Pr omise of Evolutionary Computation on Wall Str eet 193 chromosomes assumed that the standard predictor variables used in the existing models were utilized, and only the transforms were adjusted. A more complex variant allowed the predictor variables to change as well as the transform. The most sophisticated chromosome allowed for variation in functional form, introducing ideas from genetic programming.

Use of the GA for Coping with a Combinatoric Explosion of Models After we have selected a chromosome that describes the class of models we are interested in, and a fitness function to rank models, we are ready to venture out into the truly vast space of possible models. Perils and Pr omise of Evolutionary Computation on Wall Str eet 195 Let’s simplify the problem by assuming the questions of what and how to predict have been decided. These were in fact the conditions that we faced at First Quadrant. The investment strategies in place called for forecasts of particular financial variables (broad market returns for the asset allocation, stock industry groups and common factors for equity strategies). The methodology of automated data collection and forecasting with expanding window time series regressions was already institutionalized. Much of the ongoing research therefore centered on questions of what to predict with, which by itself is a very large problem. To get a feel for how large this is, consider a set of possible predictor variables and simple measurements and transforms along these lines: Number of base variables (interest rates, exchange rates, etc.)


pages: 385 words: 128,358

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

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Albert Einstein, asset allocation, Berlin Wall, Bonfire of the Vanities, Bretton Woods, buy low sell high, capital controls, central bank independence, Chance favours the prepared mind, 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 smart real money accounts like Harvard Management Company or the Yale Endowment Fund rely on diversification as their essential risk management tool.They do not have stop-losses, nor do they believe in micromanaging their portfolio.They start out by setting their asset allocation mix and then, through rebalancing, they actually increase the risk. We can illustrate this with a simple case study. Say they start out with an asset allocation mix of 50 percent equities and 50 percent bonds, and equities go down 20 percent.They now have approximately 45 percent of their portfolio in equities and 55 percent in bonds.To keep their asset allocation mix stable, they’ll go out and sell some bonds and buy some equities to get back to 50 percent in each. If the stock market drops another 20 percent, they’ll do the same thing again. Eventually, if the stock market keeps falling REAL MONEY Real money is another term for a “long-only” traditional asset manager who typically owns (long) instruments and does not short.

The simplest version is you want a carry trader, a fund that earns regular income; and you want a gamma trader, one that looks for the huge move.You want someone who’s going to make you the regular money when things are normal and quiet, and the guy who’s going to make you a lot of money when things really move. That’s how you develop a diversified portfolio. Not by diversifying through markets or by geographic regions but through how they trade. The great trades in global macro are when you combine carry with gamma.When a high yielding currency is cheap, for example, is when you can get tremendous outsized returns. THE RESEARCHER 129 Why do you think asset allocators find global macro the most difficult of the hedge fund strategies to understand? Number one, it’s not easy to assess quantitatively because it’s nonsystematic. Second, because the differences in the managers are very important in terms of how they trade rather than where they trade. Third, because the largest group of managers is in the mixed area between the guys who really shouldn’t be doing it and the guys who are doing all right but will never be superstars.

Today may be an ideal time to gain exposure to global macro managers, before the large imbalances unwind, the housing bubble pops, equities finally revert to their historical mean, the U.S. deficit becomes a real problem, existing currency regimes come unglued, global markets become uncorrelated, and the new Federal Reserve chairman, Ben Bernanke, lifts the Greenspan put.These are dream scenarios for global macro managers, who can span the globe seamlessly, reallocating risk on the fly to where the opportunities are. To reiterate, it is difficult to precisely define the global macro strategy because these elements of style drift and flexibility allow managers enhanced dexterity in times of crisis. But the ability to position themselves for outsized profits during such market inflection points is one reason why global macro managers should be included in the portfolios of all investors and asset allocators. Global macro has historically performed well, especially so during times of turmoil when other strategies and markets are doing poorly. As such, the addition of global macro hedge funds to any portfolio should serve as a hedge and a diversification tool, thus reducing risk. Given their idiosyncratic nature and open mandate, individual macro funds can offer a wide variety of returns. In 2005, for example, the returns for global macro hedge funds ranged from +57 percent to –8 percent.


pages: 425 words: 122,223

Capital Ideas: The Improbable Origins of Modern Wall Street by Peter L. Bernstein

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Albert Einstein, asset allocation, backtesting, Benoit Mandelbrot, Black-Scholes formula, Bonfire of the Vanities, Brownian motion, buy low sell high, capital asset pricing model, corporate raider, debt deflation, diversified portfolio, Eugene Fama: efficient market hypothesis, financial innovation, financial intermediation, fixed income, full employment, implied volatility, index arbitrage, index fund, interest rate swap, invisible hand, John von Neumann, Joseph Schumpeter, Kenneth Arrow, law of one price, linear programming, Louis Bachelier, mandelbrot fractal, martingale, means of production, money market fund, Myron Scholes, new economy, New Journalism, Paul Samuelson, profit maximization, Ralph Nader, RAND corporation, random walk, Richard Thaler, risk/return, Robert Shiller, Robert Shiller, Ronald Reagan, stochastic process, the market place, The Predators' Ball, the scientific method, The Wealth of Nations by Adam Smith, Thorstein Veblen, transaction costs, transfer pricing, zero-coupon bond, zero-sum game

“I think it would have been sensational, even though poorly diversified and the actual undervaluedness was suspicious.” Meanwhile, Fouse was designing another product that has become increasingly important for Wells Fargo: tactical asset allocation, a method of calculating separately the expected returns for the stock market, the bond market, and the market for cash equivalents like Treasury bills. Then the assets are shifted to the market or markets that appear relatively most attractive. Although Sharpe (and Vertin, too) was skeptical about the feasibility of this idea at first, Fouse managed to successfully combine Sharpe’s theoretical concepts with the ideas of Markowitz, Tobin, and John Burr Williams. Although the notion is buy-low-sell-high, tactical asset allocation differs from so-called market timing in two ways. First, it is a scientific method of allocating assets. Second, the idea is to buy undervalued assets and to sell overvalued assets and to wait until the market corrects the perceived misvaluations; this approach differs fundamentally from flatly declaring that “this is the bottom” or “this is the top.”

There is ERISA to regulate corporate pension funds, and there are employee savings plans that enable employees to manage their own pension funds. There are markets for options (puts and calls) and markets for futures, and markets for options on futures. There is program trading, index arbitrage, and risk arbitrage. There are managers who provide portfolio insurance and managers who offer something called tactical asset allocation. There are butterfly swaps and synthetic equity. Corporations finance themselves with convertible bonds, zero-coupon bonds, bonds that pay interest by promising to pay more interest later on, and bonds that give their owners the unconditional right to receive their money back before the bonds come due. The world’s total capital market of stocks, bonds, and cash had ballooned from only $2 trillion in 1969 to more than $22 trillion by the end of 1990; the market for stocks alone had soared from $300 billion to $55 trillion.

In 1969, convinced that professional portfolio management sorely lacked discipline, William Fouse (above right) proposed the establishment of an index fund to his boss at Mellon Bank’s trust department, and was “figuratively thrown out of the policy meeting” for his efforts. He left after this confrontation to work for McQuown and Vertin at Wells Fargo. There he led them in developing applications of the new thinking, including the dividend discount model, asset allocation, and indexing. While living on a tugboat and teaching at Berkeley, Barr Rosenberg (left) launched a consulting practice in 1969 that played a dominant role in introducing portfolio managers to applications of the theories of Sharpe, Markowitz, and Fama. He left consulting in 1985 to start his own portfolio management group, which now has some $10 billion under management. When Berkeley economist Hayne Leland (above left) found his personal finances deteriorating in 1976, he decided that “lifestyles were in danger, and it was time for invention.”

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

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asset allocation, backtesting, Black-Scholes formula, Bretton Woods, 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, equity premium, Eugene Fama: efficient market hypothesis, 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, survivorship bias, technology bubble, The Great Moderation, The Wisdom of Crowds, transaction costs, tulip mania, Vanguard fund

In the long run, getting out of the market at the peak does not guarantee that you will beat the buy-and-hold investor. 2 Chapter 19 on behavioral economics analyzes how investors’ aversion to taking losses, no matter how small, affects portfolio performance. 28 PART 1 The Verdict of History FIGURE 2–2 Average Total Real Returns after Major Twentieth-Century Market Peaks ($100 Initial Investment) STANDARD MEASURES OF RISK The risk—defined as the standard deviation of average real annual returns—for stocks, bonds, and bills based on the historical sample of over 200 years is displayed in Figure 2-3. Standard deviation is the measure of risk used in portfolio theory and asset allocation models. Although the standard deviation of stock returns is higher than for bond returns over short-term holding periods, once the holding period increases to between 15 and 20 years, stocks become less risky than bonds. Over 30-year periods, the standard deviation of a portfolio of equities falls to less than three-fourths that of bonds or bills. The standard deviation of average stock returns falls nearly twice as fast as for fixedincome assets as the holding period increases.

The square at the bottom of each curve represents the risk and return of an all-bond portfolio, while the cross at the top of the curve represents the risk and return of an all-stock portfolio. The circle falling somewhere on the curve indicates the minimum risk achievable by combining stocks and bonds. The curve that connects these points represents the risk and return of all blends of portfolios from 100 percent bonds to 100 percent stocks. This curve, called the efficient frontier, is the heart of modern portfolio analysis and is the foundation of asset allocation models. Investors can achieve any combination of risk and return along the curve by changing the proportion of stocks and bonds. Moving up the 5 Short-term Treasury securities such as bills have often enjoyed safe-haven status. Rising bond prices in a tumultuous equity market also occurred during the October 19, 1987, stock market crash, but much of the rise then was predicated on the (correct) belief that the Fed would lower short-term rates. 6 This section, which contains some advanced material, can be skipped without loss of continuity.

Nevertheless, these bonds may be an attractive alternative for investors who do not want to assume the short-term risks of stocks but fear loss of purchasing power in bonds. In 20 percent of all 10-year periods from 1926, stocks have fallen short of a 2.0 percent real return. For most long-term investors, inflation-indexed bonds should dominate nominal bonds in a portfolio. 8 For an excellent review of this literature see Luis M. Viceira and John Y. Campbell, Strategic Asset Allocation: Portfolio Choice for Long-Term Investors, New York: Oxford University Press, 2002. Also see Nicholas Barberis, “Investing for the Long Run When Returns Are Predictable,” Journal of Finance, vol. 55 (2000), pp. 225–264. Paul Samuelson has shown that mean reversion will increase equity holdings if investors have a risk aversion coefficient greater than unity, which most researchers find is the case.


pages: 426 words: 115,150

Your Money or Your Life: 9 Steps to Transforming Your Relationship With Money and Achieving Financial Independence: Revised and Updated for the 21st Century by Vicki Robin, Joe Dominguez, Monique Tilford

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asset allocation, Buckminster Fuller, buy low sell high, credit crunch, disintermediation, diversification, diversified portfolio, fiat currency, financial independence, fixed income, fudge factor, full employment, Gordon Gekko, high net worth, index card, index fund, job satisfaction, Menlo Park, money market fund, Parkinson's law, passive income, passive investing, profit motive, Ralph Waldo Emerson, Richard Bolles, risk tolerance, Ronald Reagan, Silicon Valley, software patent, strikebreaker, Thorstein Veblen, Vanguard fund, zero-coupon bond

Diversify across many asset classes. This will reduce portfolio risk and probably increase returns as well.” Designing Your Own ʺENOUGH . . . AND THEN SOMEʺ FI3 Portfolio Your “portfolio” is a fancy way of saying the sum of your investments across “asset classes”—which simply means types of investment vehicles such as cash, bonds, stocks, real estate, foreign currency and commodities. Asset allocation is the art and science of distributing your nest egg across various classes to balance risk and reward. Instead of putting all your eggs in one basket, you are wisely limiting your market risk by spreading your money across various asset classes. This is a smart, sensible and time-tested strategy. By using index funds, you can allocate your capital across various asset classes. This enables you to reduce volatility without giving up investment performance.

For example, a lifestyle fund might divide its holdings among the U.S stock market, the U.S. bond market, the international stock index and a variety of other options. This approach takes the guesswork out of where and how to invest your capital, which is often the reason many people avoid the stock market in the first place. For those who plan on sticking with the FI investment program yet are willing to take some risk with a portion of their capital, this would be a very viable option. These funds enable you to pick the asset allocation that fits your long-term investment objective. Best of all, the fund automatically rebalances to maintain a consistent allocation among stocks, bonds and short-term investments. Puzzling through these options, through the risks and rewards of different paths, Sally H. decided to split her investment portfolio using the “enough . . . and then some” description of the nest egg you have at Crossover.

Here’s his explanation: Mark’s suggestions for Your NEW FI Investment Strategy The most conservative approach for this strategy would be to use the Life-Strategy Income Fund, the first of the four Vanguard Funds. Although marketed as a fund for those in retirement, it is also applicable for those who are FI and no longer working for money. This fund seeks current income and has some growth of capital. The fund applies a fixed formula that over time should reflect an asset allocation of approximately 60 percent of the fund’s assets to bonds, 20 percent to short-term reserves and 20 percent to common stocks. A balanced approach would be to use the Life-Strategy Conservative Growth Fund. This balanced approach literally balances your need for long-term growth of capital along with your need for income. The fund is allocated approximately as follows: 40 percent of the fund’s assets to bonds, 20 percent to short-term fixed income reserves and 40 percent to common stocks.


pages: 264 words: 115,489

Take the money and run: sovereign wealth funds and the demise of American prosperity by Eric Curt Anderson

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asset allocation, banking crisis, Bretton Woods, business continuity plan, business intelligence, business process, collective bargaining, corporate governance, credit crunch, currency manipulation / currency intervention, currency peg, diversified portfolio, fixed income, floating exchange rates, housing crisis, index fund, Kenneth Rogoff, open economy, passive investing, profit maximization, profit motive, random walk, reserve currency, risk tolerance, risk-adjusted returns, risk/return, Ronald Reagan, sovereign wealth fund, the market place, The Wealth of Nations by Adam Smith, too big to fail, Vanguard fund

“Second, transactions involving investment by sovereign wealth funds, as with other types of foreign investment, may raise legitimate national security concerns.” And, third, “sovereign wealth funds may raise concerns related to financial stability. Sovereign wealth funds can represent large, concentrated, and often nontransparent positions in certain markets and asset classes. Actual shifts in their asset allocations could cause market volatility. In fact, even perceived shifts or rumors can cause volatility as the market reacts to what it perceives sovereign wealth funds to be doing.”77 Undersecretary McCormick’s remarks appear to represent the Bush administration’s overarching policy concerns vis-à-vis the emerging purchasing power of sovereign wealth funds. Indeed, the primary points offered in McCormick’s presentation were echoed in early December 2007 by Christopher Cox, Chairman of the Securities and Exchange Commission (SEC).

As noted previously, Chinese officials have repeatedly promised that much of CIC’s offshore activity would be limited to the purchase of index funds120 and a portfolio approach— making many small purchases of equities, bonds, and other investment options.121 By February 2008, Lou Jiwei had, on more than one occasion, told Western audiences the China Investment Corporation would focus on “portfolios” rather than target individual firms.122 In March 2008, Jesse Wang made essentially the same promise, declaring the CIC would pursue “highly diversified assets allocation . . . [This] will help spread the risk as much as possible and increase returns.”123 Even as Beijing sets forth on a path intended to maximize returns while minimizing foreign political sensitivities, there has been no shortage of would-be consultants willing to offer the CIC free advice on the most lucrative path to follow. For instance, a strategist at Nomura Securities suggested the Chinese consider the auto industry and a selection of insurance companies.

The primary risk is that sovereign wealth funds could provoke a new wave of protectionism, which could be very harmful to the U.S. and global economies. 2. Transactions involving investment by sovereign wealth funds, as with other types of foreign investment, may raise legitimate national security concerns. 3. Sovereign wealth funds may raise concerns related to financial stability. Sovereign wealth funds can represent large, concentrated, and often nontransparent positions in certain markets and asset classes. Actual shifts in their asset allocations can cause market volatility. In fact, even perceived shifts or rumors can cause volatility as the market reacts to what it perceives sovereign wealth funds to be doing117 This list of concerns replicated remarks McCormick had made before the Senate Committee on Banking, Housing, and Urban Affairs in mid-November 2007. Intent on preventing the passage of legislation that might drive away foreign investment, the Bush administration was continuing to focus attention on the evils of “protectionism.”

A Primer for the Mathematics of Financial Engineering by Dan Stefanica

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asset allocation, Black-Scholes formula, capital asset pricing model, constrained optimization, delta neutral, discrete time, Emanuel Derman, implied volatility, law of one price, margin call, quantitative trading / quantitative finance, Sharpe ratio, short selling, time value of money, transaction costs, volatility smile, yield curve, zero-coupon bond

The expected values, standard deviations, and correlations of the rates of return of the assets are: 0.08; (11 0.12; (12 0.16; (13 0.05; (14 /-L1 /-L2 /-L3 /-L4 Se- qT -C, - Ke- rT - if C, if Se(r-q)T Se(r-q)T < > K· K' (iii) Show that f(x) is a strictly increasing function and S e -qT - 0.25; - 0.25; 0.25; 0, \j i = 1 : 3. 0.25; P1,2 0.25; P2,3 0.30; P1,3 0.20; Pi,4 { - - K e- rT -0 < f(x) < - 0 < f(x) < Se- qT Se- qT - 0 if 0,' if Se(r-q)T Se(r-q)T <_ K', > K. (iv) For w~~t range of call option values does the problem f(x) = 0 have a posItive solution? Compare your result to the range g' . (3.92). Iven In (i) Find the asset allocation for a minimal variance portfolio with 12% expected rate of return; (ii) Find the asset allocation for a maximum expected return portfolio with standard deviation of the rate of return equal to 24%. 5. A .three mon~hs a~-~he-money call on an underlying asset with spot pnce 30 paymg d:vldend~ continuously at a 2% rate is worth $2.5. Assume that the nsk free mterest rate is constant at 6%. (i). 3. Use Newton's method to find the yield of a five year semiannual coupon bond with 3.375% coupon rate and price 100 What are the duration and convexity of the bond?

In other words, a portfolio where th~ :veight of ~sset i in the portfolio is equal to WO,i, for i = 1 : 4, is the mlllImum vanance portfolio with rate of return J-Lp. 0 Example: Find a minimal variance portfolio with 11:5% .expected rate. of return, if four assets can be traded to set up the portfoho, gIVen the follOWIng data on the rates of return of the assets: J-LI J-L2 J-L3 J-L4 0.09; 0"1 0.12; 0"2 0.15; 0"3 0.06; 0"4 = = = 0.2; 0.3; 0.35; 0.15; PI,2 P2,3 PI,3 pi,4 - 0.5; 0.25; 0.35; 0, \;j i = WO,4 An,l An,2 The asset allocation for a minimal variance portfolio with 11.5% expected rate of return is as follows: 54.75% in asset 1, 44.03% in asset 2, 13.5% in asset 3, while shorting an amount of asset 4 equal to 12.29% of the value of the portfolio. For example, if the value of the portfolio is $1,000,000, then $122,872 of asset 4 is shorted (borrowed and sold for cash) $547,452 is invested in asset 1, $440,377 is invested in asset 2, and $135,042 is invested in asset 3.


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Fortune's Formula: The Untold Story of the Scientific Betting System That Beat the Casinos and Wall Street by William Poundstone

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Albert Einstein, anti-communist, asset allocation, beat the dealer, Benoit Mandelbrot, Black-Scholes formula, Brownian motion, buy low sell high, capital asset pricing model, Claude Shannon: information theory, computer age, correlation coefficient, diversified portfolio, Edward Thorp, en.wikipedia.org, Eugene Fama: efficient market hypothesis, high net worth, index fund, interest rate swap, Isaac Newton, Johann Wolfgang von Goethe, John Meriwether, John von Neumann, Kenneth Arrow, Long Term Capital Management, Louis Bachelier, margin call, market bubble, market fundamentalism, Marshall McLuhan, Myron Scholes, New Journalism, Norbert Wiener, offshore financial centre, Paul Samuelson, publish or perish, quantitative trading / quantitative finance, random walk, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Shiller, Ronald Reagan, Rubik’s Cube, short selling, speech recognition, statistical arbitrage, The Predators' Ball, The Wealth of Nations by Adam Smith, transaction costs, traveling salesman, value at risk, zero-coupon bond, zero-sum game

Maxwell’s demon is only redistributing entropy and energy. In 1974 Paul Samuelson wrote that a high-PQ trader “is in effect possessed of a ‘Maxwell’s Demon’ who tells him how to make capital gains from his effective peek into tomorrow’s financial page reports.” Like Maxwell’s demon, Shannon’s stock system turns randomness into profit. Shannon’s “demon” partitions his wealth into two assets. As the asset allocation crosses the 50 percent line from either direction, the demon makes a trade, securing an atom-sized profit or making an atom-sized purchase—and it all adds up in the long run. The “trick” behind this is simple. The arithmetic mean return is always higher than the geometric mean. Therefore, a volatile stock with zero geometric mean return (as assumed here) must have a positive arithmetic mean return.

Latané pointed out that “it is difficult to identify the underlying utilities and to tell exactly when the utilities are being maximized” in the case of a mutual fund or pension fund. The fund manager is cooking for an army. It’s impractical to gauge everyone’s taste for salt—or risk. Thorp was managing money not only for wealthy individuals but for corporate pensions and Harvard University’s endowment. For most of these investors, Princeton-Newport was just one of many investments. The investors could do their own asset allocation. It was Thorp’s job to provide an attractive financial product. Undoubtedly, investors judged the fund largely by its risk-adjusted return. In articles published in 1972 and 1976, Harry Markowitz made this point most forcefully. The utility function of a long-term investor should be denominated in compound return, not terminal wealth, Markowitz suggested. Imagine you’re choosing between two mutual funds.

That is why the Kelly system has more relevance to an in-and-out trader than a typical small investor. Economists are not primarily in the business of studying gambling systems. Nor did the exotic doings of arbitrageurs attract much attention from the theorists of Samuelson’s generation. The main issue of academic interest on which the Kelly system appeared to have something new to say was the asset allocation problem of the typical investor. How much of your money should you put in risky, high-return stocks, and how much in low-risk, low-return investments like bonds or savings accounts? The Kelly answer is to put all of your money in stocks. In fact, several authors have concluded that the index fund investor is justified in using a modest degree of leverage. (Though the stock market is subject to crashes, and though many an individual stock has become worthless, none of the U.S. stock indexes has ever hit zero.)


pages: 345 words: 86,394

Frequently Asked Questions in Quantitative Finance by Paul Wilmott

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Albert Einstein, asset allocation, beat the dealer, Black-Scholes formula, Brownian motion, butterfly effect, 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, 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

The work later won Markowitz a Nobel Prize for Economics but is rarely used in practice because of the difficulty in measuring the parameters volatility, and especially correlation, and their instability. 1963 Sharpe, Lintner and Mossin William Sharpe of Stanford, John Lintner of Harvard and Norwegian economist Jan Mossin independently developed a simple model for pricing risky assets. This Capital Asset Pricing Model (CAPM) also reduced the number of parameters needed for portfolio selection from those needed by Markowitz’s Modern Portfolio Theory, making asset allocation theory more practical. See Sharpe (1963), Lintner (1963) and Mossin (1963). 1966 Fama Eugene Fama concluded that stock prices were unpredictable and coined the phrase “market efficiency.” Although there are various forms of market efficiency, in a nutshell the idea is that stock market prices reflect all publicly available information, that no person can gain an edge over another by fair means.

The expected variance, k time steps in the future, then behaves likeE[vn+k] = w0 + (vn - w0)(α + β)n. Since α + β < 1 this is exponentially decay of the average to its mean. A much nicer, more realistic, time dependence than we get from the EWMA model. In GARCH(p, q) the (p, q) refers to there being p past variances and q past returns in the estimate: Why? Volatility is a required input for all classical option-pricing models, it is also an input for many asset-allocation problems and risk estimation, such as Value at Risk. Therefore it is very important to have a method for forecasting future volatility. There is one slight problem with these econometric models, however. The econometrician develops his volatility models in discrete time, whereas the option-pricing quant would ideally like a continuous-time stochastic differential equation model. Fortunately, in many cases the discrete-time model can be reinterpreted as a continuous-time model (there is weak convergence as the time step gets smaller), and so both the econometrician and the quant are happy.

Statistical studies show that there is significant kurtosis (fat tails) and some skewness (asymmetry). Whether this matters or not depends on several factors:• Are you holding stock for speculation or are you hedging derivatives? • Are the returns independent and identically distributed (i.i.d.), albeit non normally? • Is the variance of the distribution finite? • Can you hedge with other options? Most basic theory concerning asset allocation, such as Modern Portfolio Theory, assumes that returns are normally distributed. This allows a great deal of analytical progress to be made since adding random numbers from normal distributions gives you another normal distribution. But speculating in stocks, without hedging, exposes you to asset direction; you buy the stock since you expect it to rise. Assuming that this stock isn’t your only investment then your main concern is for the expected stock price in the future, and not so much its distribution.


pages: 212 words: 70,224

How to Retire the Cheapskate Way by Jeff Yeager

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

The easiest dollar you’ll ever earn is the one you’ve already earned and don’t lose or waste. There are four aspects to this rule: Develop a proclivity for safe(r) investments over more risky ones. After all, if you can live comfortably on less money, you don’t need to gamble so aggressively on high-risk investments. The preservation of capital becomes the overriding consideration. Create an individualized asset allocation plan, a plan for what types of investments make sense for you and involve whatever level of risk you can tolerate and still sleep well at night. Remember, in the very act of diversification there is, almost without exception, greater security. “Ton-tog-an-y. Isn’t that Lakota for ‘Don’t put all your eggs in one basket’?” Maintain appropriate insurances to protect yourself and your assets.

“Ultimately, this tug of war more accurately depicts the average American’s spending patterns throughout retirement.” By Bernicke’s use of the phrase “tug-of-war,” one might imagine that the tendency to naturally spend less as we age (as reflected in the USBLS survey) is pretty much a wash with a projected annual inflation rate of 3 or 4 percent. In other words, you might expect that in the end, the tug-of-war ends in a tie. You might need a Cheapskate Intervention if your idea of asset allocation is to bet on the same horse to win, place, and show. But when you apply the suppositions behind reality retirement planning to some hypothetical situations, the outcome is anything but a Mexican standoff. In his article, Bernicke uses the example of a couple with an $800,000 retirement nest egg and a need for $60,000 in after-tax spending money in their first year of retirement, which they hope will be at age fifty-five.


pages: 369 words: 128,349

Beyond the Random Walk: A Guide to Stock Market Anomalies and Low Risk Investing by Vijay Singal

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3Com Palm IPO, Andrei Shleifer, asset allocation, capital asset pricing model, correlation coefficient, cross-subsidies, Daniel Kahneman / Amos Tversky, diversified portfolio, endowment effect, fixed income, index arbitrage, index fund, information asymmetry, liberal capitalism, locking in a profit, Long Term Capital Management, loss aversion, margin call, market friction, market microstructure, mental accounting, merger arbitrage, Myron Scholes, new economy, prediction markets, price stability, profit motive, random walk, Richard Thaler, risk-adjusted returns, risk/return, selection bias, Sharpe ratio, short selling, survivorship bias, transaction costs, Vanguard fund

Moreover, industries with no related futures markets are likely to show greater momentum than industries where information regarding real assets is aggregated in futures prices. Industry portfolios constructed in this manner generate returns that may be much larger than the S&P 500 return. Description Investment practitioners believe that asset allocation among bonds, domestic stocks, and foreign stocks should be altered over time depending on individual circumstances and economic conditions.1 This chapter proposes taking asset allocation a step further, to allocation among different industries. One industry may be hot today and another may be hot next month depending on changing fads, individual preferences, national requirements, or political expediency. For example, after the terrorist attacks on September 11, 2001, the defense and security industry did exceptionally well, as demand for such equipment and personnel increased.

Beyond the Random Walk: A Guide to Stock Market Anomalies and Low-Risk Investing VIJAY SINGAL, PH.D., CFA OXFORD UNIVERSITY PRESS BEYOND THE RANDOM WALK Financial Management Association Survey and Synthesis Series The Search for Value: Measuring the Company’s Cost of Capital Michael C. Ehrhardt Managing Pension Plans: A Comprehensive Guide to Improving Plan Performance Dennis E. Logue and Jack S. Rader Efficient Asset Management: A Practical Guide to Stock Portfolio Optimization and Asset Allocation Richard O. Michaud Real Options: Managing Strategic Investment in an Uncertain World Martha Amram and Nalin Kulatilaka Beyond Greed and Fear: Understanding Behavioral Finance and the Psychology of Investing Hersh Shefrin Dividend Policy: Its Impact on Form Value Ronald C. Lease, Kose John, Avner Kalay, Uri Loewenstein, and Oded H. Sarig Value Based Management: The Corporate Response to Shareholder Revolution John D.


pages: 421 words: 128,094

King of Capital: The Remarkable Rise, Fall, and Rise Again of Steve Schwarzman and Blackstone by David Carey; John E. Morris; John Morris

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activist fund / activist shareholder / activist investor, asset allocation, banking crisis, Bonfire of the Vanities, 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

Beginning in the early 2000s many state pension funds were required to disclose returns on individual private equity and venture capital funds in which they had invested, making the returns a matter of public record for the first time. 10 Blackstone’s 2002 fund: CalPERS Fund Report as of Dec. 31, 2008; Oregon Public Employees’ Retirement Fund, Alternative Equity Portfolio as of Mar. 31, 2009. 11 By the late 1990s, banks: Center for Private Equity and Entrepreneurship, Tuck School of Business at Dartmouth, Note on Private Equity Asset Allocation, Case #5-0015, updated Aug. 18, 2003 (hereafter Note on Allocation), 14. 12 The typical pension fund: 2009 Wilshire Report on State Retirement Systems: Funding Levels and Asset Allocations, Wilshire Associates, Inc., 11–12; Note on Allocation, 2–3. 13 Giant pensions: Ibid., 1; CalPERS Fund Report as of Dec. 31, 2005. 14 Between 2003 and 2008: 2009 Wilshire Report on State Retirement Systems, 11. 15 But those whose profits: Heino Meerkatt, John Rose, Michael Brig, Heinrich Liechenstein, M.

The colossal sell-off of stocks and bonds that ensued only compounded private equity’s fund-raising problems. As investors dumped stocks, bonds, and other liquid assets at fire-sale prices, the value of their overall portfolios sank relative to their private equity holdings, which were valued based on their long-term potential and thus didn’t slump as much. As a result, private equity rose as a percentage of the investors’ total assets, which threw the investors’ asset allocations out of whack. Private equity’s investors had to curtail new commitments to buyout funds in order to rebalance their accounts. Private equity also faced another enormous problem. More than $800 billion of leveraged bank loans and junk bonds were due for refinancing from 2012 to 2014. Even if the economy turned up by then, many companies might still be worth less than the bloated sums paid for them, meaning that there might not be enough collateral to refinance their debt.


pages: 461 words: 128,421

The Myth of the Rational Market: A History of Risk, Reward, and Delusion on Wall Street by Justin Fox

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activist fund / activist shareholder / activist investor, Albert Einstein, Andrei Shleifer, asset allocation, asset-backed security, bank run, beat the dealer, Benoit Mandelbrot, Black-Scholes formula, Bretton Woods, Brownian motion, capital asset pricing model, card file, Cass Sunstein, collateralized debt obligation, complexity theory, corporate governance, corporate raider, Credit Default Swap, credit default swaps / collateralized debt obligations, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, discovery of the americas, diversification, diversified portfolio, Edward Glaeser, Edward Thorp, endowment effect, Eugene Fama: efficient market hypothesis, experimental economics, financial innovation, Financial Instability Hypothesis, fixed income, floating exchange rates, George Akerlof, Henri Poincaré, Hyman Minsky, implied volatility, impulse control, index arbitrage, index card, index fund, information asymmetry, invisible hand, Isaac Newton, John Meriwether, John Nash: game theory, John von Neumann, joint-stock company, Joseph Schumpeter, Kenneth Arrow, libertarian paternalism, linear programming, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, market bubble, market design, Myron Scholes, New Journalism, Nikolai Kondratiev, Paul Lévy, Paul Samuelson, pension reform, performance metric, Ponzi scheme, prediction markets, pushing on a string, quantitative trading / quantitative finance, Ralph Nader, RAND corporation, random walk, Richard Thaler, risk/return, road to serfdom, Robert Bork, Robert Shiller, Robert Shiller, rolodex, Ronald Reagan, shareholder value, Sharpe ratio, short selling, side project, Silicon Valley, South Sea Bubble, statistical model, The Chicago School, The Myth of the Rational Market, The Predators' Ball, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas L Friedman, Thorstein Veblen, Tobin tax, transaction costs, tulip mania, value at risk, Vanguard fund, Vilfredo Pareto, volatility smile, Yogi Berra

His ideas began to have some impact in his lifetime, and after his death in 1947, they took off. Books directly or indirectly descended from Fisher’s work now adorn the desks of hedge fund managers, pension consultants, financial advisers, and do-it-yourself investors. The increasingly dominant quantitative side of the financial world—that strange wonderland of portfolio optimization software, enhanced indexing, asset allocators, credit default swaps, betas, alphas, and “model-derived” valuations—is a territory where Professor Fisher would feel intellectually right at home. He is perhaps not the father, but certainly a father of modern Wall Street. Hardly anyone calls him that, though. Economists honor Fisher for his theoretical breakthroughs, but outside the discipline his chief claim to lasting fame is the horrendous stock market advice he proffered in the late 1920s.

Bill Sharpe, while he didn’t actually start a company of his own until the 1990s, was an influential consultant to pension funds and money managers. It wasn’t just the consultants and research shops. San Francisco’s Wells Fargo Investment Advisors built upon its pioneering indexing work to become what was in 2008, under the name Barclays Global Investors, the biggest money manager on the planet. Number two, State Street Global, was a big indexer and asset allocator as well.14 Every other money manager of any size in the world now uses at least some of the quantitative tools introduced in the 1970s by finance professors. What’s more, one 1970s quant tool made it far beyond the money management industry. Armed with Ibbotson’s measure of the equity risk premium and Barra’s (or some other firm’s) measure of a stock’s riskiness in relation to the overall market, one could now calculate any publicly traded company’s cost of capital.

“They don’t want to hear about theory,” complained Fischer Black of Fama and his coauthor Kenneth French, “especially theory suggesting that certain factors or securities are mispriced.”5 Two efficient market skeptics from the University of Illinois soon offered such a theory to explain the Fama-French results. Using different statistical techniques and a longer data sample, Louis K. C. Chan and Josef Lakonishok found that beta actually worked well in explaining stock market behavior from 1926 through 1982. It was only after 1982 that it ceased to fit the data. Chan and Lakonishok proposed that what changed the results after 1982 was the rise of investment strategies built around CAPM—indexing, asset allocation, beta-based performance measurement, and the like. The behavior of investors had changed, which in turn had changed the nature of investment returns. The practical triumph of the capital asset model had weakened its predictive power. Starting in the late 1970s, Chan and Lakonishok found, stocks that belonged to the S&P 500 index dramatically outperformed the rest of the market. Only 2 percent of the equity investments of the top two hundred pension funds were indexed to the S&P in 1980, they pointed out.


pages: 504 words: 126,835

The Innovation Illusion: How So Little Is Created by So Many Working So Hard by Fredrik Erixon, Bjorn Weigel

Airbnb, Albert Einstein, asset allocation, autonomous vehicles, barriers to entry, Basel III, Bernie Madoff, bitcoin, Black Swan, blockchain, BRICs, Burning Man, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, Clayton Christensen, Colonization of Mars, commoditize, corporate governance, corporate social responsibility, creative destruction, crony capitalism, dark matter, David Graeber, David Ricardo: comparative advantage, discounted cash flows, distributed ledger, Donald Trump, Elon Musk, Erik Brynjolfsson, fear of failure, first square of the chessboard / second half of the chessboard, Francis Fukuyama: the end of history, George Gilder, global supply chain, global value chain, Google Glasses, Google X / Alphabet X, Gordon Gekko, high net worth, hiring and firing, Hyman Minsky, income inequality, income per capita, index fund, industrial robot, Internet of things, Jeff Bezos, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, joint-stock company, Joseph Schumpeter, Just-in-time delivery, Kevin Kelly, knowledge economy, labour market flexibility, laissez-faire capitalism, lump of labour, Lyft, manufacturing employment, Mark Zuckerberg, market design, Martin Wolf, mass affluent, means of production, Mont Pelerin Society, Network effects, new economy, offshore financial centre, pensions crisis, Peter Thiel, Potemkin village, price mechanism, principal–agent problem, Productivity paradox, QWERTY keyboard, RAND corporation, Ray Kurzweil, rent-seeking, risk tolerance, risk/return, Robert Gordon, Ronald Coase, Ronald Reagan, savings glut, Second Machine Age, secular stagnation, Silicon Valley, Silicon Valley startup, Skype, sovereign wealth fund, Steve Ballmer, Steve Jobs, Steve Wozniak, technological singularity, telemarketer, The Chicago School, The Future of Employment, The Nature of the Firm, The Wealth of Nations by Adam Smith, too big to fail, total factor productivity, transaction costs, transportation-network company, tulip mania, Tyler Cowen: Great Stagnation, University of East Anglia, unpaid internship, Vanguard fund, Yogi Berra

To take just one example, Norway’s SWF alone manages about $860 billion and owns 1.3 percent of all corporate equity in the world.24 SWFs will most likely expand over the foreseeable future and continue to mitigate economic booms and busts for their government masters. Their growth, with 7 percent compound annual growth rate until 2020, according to PwC, will continue, with the total SWF volume expected to reach $9 trillion by the same year.25 Their strategies for asset allocation will likely continue along that trend as well. They will go on investing in foreign currencies like the greenback, the euro and the Swiss franc. Wall Street, Nasdaq, the London Stock Exchange, and other key stock markets will get a good portion of their capital as well. Investment in private companies and infrastructure are also favored investment targets – all the more so recently as their traditional assets have become more volatile.

The Norwegian government exercises control over the exploitation of energy reserves through Statoil, co-ownership of energy transport infrastructure, and through its role as regulator of transport prices, licenses, resource exhaustion, and more. It also taxes energy production, and quite heavily too. Hence, the conduct of the fund is an integral part of a system of political management. If that is the political anchor of Norway’s SWF, imagine, then, how the SWFs in less open and transparent countries are run. Politics likely motivates the asset allocation of SWFs too. Simply put, they do not have a capitalist agenda, and given how much revenues for SWFs fluctuate with the course of commodity prices, they can also be unreliable owners, suddenly needing to change track. And it is not only the revenue flutuations that divert attention from a capitalist agenda. In an attempt to appease the public during the Arab Spring of 2011, to take one example, the Gulf states suddenly and radically cut allocations to foreign investments.

The calls to “balance fluctuations” went out of the window virtually overnight. Despite increased revenues, up 6 percent from 2011 to 2012, the Gulf states cut transfers to SWFs by almost 40 percent. At the same time, SWF investments in the Gulf rose to 54 percent, up from 33 percent the previous year.28 It is possible, at least theoretically, that this change was for strict investment reasons, but in reality the sudden change of asset allocation was politically motivated. The SWFs had to return capital back home in order to help governments stem opposition. The sovereign wealth funds have done much to burnish their political credentials. In the aftermath of the financial crisis, their critics were quickly silenced when Western corporates pleaded with SWFs to invest and to save credit-dry Western companies from bankruptcy. Companies desperate for funding, neglected by banks under strain, did what they could to survive, and perhaps that is why so many kowtowed to SWFs, even calling them “white knights.”29 Like every actor with liquidity, big money can be created in crises and downturns, but its role in Western corporate ownership is turning into a problem as the model presupposes that capitalism can work even if the financial impulses come from government offices.


pages: 364 words: 101,286

The Misbehavior of Markets by Benoit Mandelbrot

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Albert Einstein, asset allocation, Augustin-Louis Cauchy, Benoit Mandelbrot, Big bang: deregulation of the City of London, Black-Scholes formula, British Empire, Brownian motion, buy low sell high, capital asset pricing model, carbon-based life, discounted cash flows, diversification, double helix, Edward Lorenz: Chaos theory, Elliott wave, equity premium, Eugene Fama: efficient market hypothesis, Fellow of the Royal Society, full employment, Georg Cantor, Henri Poincaré, implied volatility, index fund, informal economy, invisible hand, John Meriwether, John von Neumann, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, market bubble, market microstructure, Myron Scholes, new economy, paper trading, passive investing, Paul Lévy, Paul Samuelson, Plutocrats, plutocrats, price mechanism, quantitative trading / quantitative finance, Ralph Nelson Elliott, RAND corporation, random walk, risk tolerance, Robert Shiller, Robert Shiller, short selling, statistical arbitrage, statistical model, Steve Ballmer, stochastic volatility, transfer pricing, value at risk, Vilfredo Pareto, volatility smile

They instinctively realize that the market is very, very risky, riskier than the standard models say. So, to compensate them for taking that risk, they naturally demand and often get a higher return. The same reasoning—that people instinctively understand the market is very risky—helps explain why so much of the world’s wealth remains in safe cash, rather than in anything riskier. The Wall Street mantra is asset allocation: Deciding how to divide your portfolio among cash, bonds, stocks, and other asset classes is far more important than the specific stocks or bonds you pick. A typical broker’s recommendation, based on Markowitz-Sharpe portfolio theory, is 25 percent cash, 30 percent bonds, and 45 percent stocks. But, according to a study by the Organization for Economic Cooperation and Development, most people do not think that way.

Multifractals should not be viewed as an “ad-hoc” structure but as the natural counterpart of two classical tools; the generating function (that is, the sequence of moments) and spectral analysis. Their parameters are intrinsic. Chapter XII Ten Heresies of Finance 230 “Consider the so-called Equity Premium Puzzle…” A good summary of their initial paper, and the difficulty it had in getting published, is provided in Mehra and Prescott 2003. 231 “The same reasoning…” For more on this, see Babeau, André and Sbano 2002. In fact, the precise asset allocation recommendations can vary from that 25-30-45 mix, depending on what the market is doing at any particular time. 232 “The ultimate fear…” See Embrechts, Klüppelberg and Mikosch 1997. 234 “Concentration is common…” See Lantsman, Major and Mangano 2002. 235 “One day when I was working…” Alexander’s “Filter” method attracted a great deal of attention–and similar methods have been devised and tried since his day.


pages: 375 words: 105,067

Pound Foolish: Exposing the Dark Side of the Personal Finance Industry by Helaine Olen

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asset allocation, Bernie Madoff, Cass Sunstein, Credit Default Swap, David Brooks, delayed gratification, diversification, diversified portfolio, Donald Trump, Elliott wave, en.wikipedia.org, estate planning, financial innovation, Flash crash, game design, greed is good, high net worth, impulse control, income inequality, index fund, London Whale, Mark Zuckerberg, money market fund, mortgage debt, oil shock, payday loans, pension reform, Ponzi scheme, quantitative easing, Ralph Nader, RAND corporation, random walk, Richard Thaler, Ronald Reagan, Saturday Night Live, too big to fail, transaction costs, Unsafe at Any Speed, upwardly mobile, Vanguard fund, wage slave, women in the workforce, working poor, éminence grise

“When I look into the abyss of retirement income security, I find them to be very feeble efforts by the government to try to stem the crisis.” In the written testimony Ghilarducci submitted, her words were even more prescient. “Shifting responsibility to workers and bullying them from the pulpit to save like professional money managers…will encourage the high income, not the low, to save in individualistic ways, grow up a whole industry of vendors, and divert human activity toward tending to asset allocation and mutual fund performance.” How accurate was Ghilarducci? Let’s turn to the numbers. As of the end of 2011, we had $17.9 trillion in retirement savings divided among individual retirement accounts ($4.9 trillion), defined contribution plans ($4.5 trillion), defined benefit plans ($2.4 trillion), government plans ($4.5 trillion), and with the remainder in annuity reserves, a number that is expected to increase significantly over the coming decade.

You can lose half your wealth,” he said to the knowing laughter of the crowd. When the floor opened for audience participation, I realized women are asking the same questions I hear at almost every financial seminar I attended, either in person or via webinar, the seminars where the vast majority of attendees are almost always male. “How would you recommend the average investor prepare for the end of quantitative easing?” asked one. Another inquired how asset allocation fit in with risk management since pretty much all categories of investment had fallen significantly during the 2008 economic crash. About the only thing female-specific about this session is that the vast majority of the attendees and all of those asking questions were women. A few weeks before the Citi breakfast, I met with Linda Descano, who I admit I liked immediately. Descano is slightly heavyset, speaks softly, and is well made up and well dressed, though not too well dressed.


pages: 261 words: 86,905

How to Speak Money: What the Money People Say--And What It Really Means by John Lanchester

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asset allocation, Basel III, Bernie Madoff, Big bang: deregulation of the City of London, bitcoin, Black Swan, blood diamonds, Bretton Woods, BRICs, Capital in the Twenty-First Century by Thomas Piketty, Celtic Tiger, central bank independence, collapse of Lehman Brothers, collective bargaining, commoditize, creative destruction, credit crunch, Credit Default Swap, crony capitalism, Dava Sobel, David Graeber, disintermediation, double entry bookkeeping, en.wikipedia.org, estate planning, financial innovation, Flash crash, forward guidance, Gini coefficient, global reserve currency, high net worth, High speed trading, hindsight bias, income inequality, inflation targeting, interest rate swap, Isaac Newton, Jaron Lanier, joint-stock company, joint-stock limited liability company, Kodak vs Instagram, liquidity trap, London Interbank Offered Rate, London Whale, loss aversion, margin call, McJob, means of production, microcredit, money: store of value / unit of account / medium of exchange, moral hazard, Myron Scholes, negative equity, neoliberal agenda, New Urbanism, Nick Leeson, Nikolai Kondratiev, Nixon shock, Northern Rock, offshore financial centre, oil shock, open economy, paradox of thrift, Plutocrats, plutocrats, Ponzi scheme, purchasing power parity, pushing on a string, quantitative easing, random walk, rent-seeking, reserve currency, Richard Feynman, Richard Feynman, Right to Buy, road to serfdom, Ronald Reagan, Satoshi Nakamoto, security theater, shareholder value, Silicon Valley, six sigma, South Sea Bubble, sovereign wealth fund, Steve Jobs, survivorship bias, The Chicago School, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, trickle-down economics, Washington Consensus, wealth creators, working poor, yield curve

The words “guaranteed profit” are magical in finance, and so arbitrage is a beloved feature of the markets, appearing in very many complicated forms, in every imaginable cranny of every imaginable market. asset allocation An approach to investment that has grown in popularity with modern theories of efficient markets. If it’s impossible to do a better job of picking and choosing shares than the market does—which is what many studies of the stock market claim to have proved—it follows that you should save the time you spend on picking stocks and spend it instead on choosing the right areas of the market to be in. Don’t think about BP versus Shell versus Exxon, think about whether you should be in oil at all; more generally, think about the balance between stocks and bonds and property and commodities, developed and emerging markets, and then allocate your assets accordingly, investing preferably via cheap pooled funds wherever possible. This balance of asset allocation is, in the modern theory of investing, the most important thing to get right.


pages: 297 words: 91,141

Market Sense and Nonsense by Jack D. Schwager

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3Com Palm IPO, asset allocation, Bernie Madoff, Brownian motion, collateralized debt obligation, commodity trading advisor, computerized trading, conceptual framework, correlation coefficient, Credit Default Swap, credit default swaps / collateralized debt obligations, Daniel Kahneman / Amos Tversky, 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

For example, if markets are generally experiencing choppy trading-range conditions, countertrend strategies are likely to do very well, while trend-following approaches get whipsawed. If market conditions then change so that there are many prevalent trends, trend-following methods will be very profitable, while countertrend traders will suffer losses. Rebalancing keeps the asset allocation among the different market strategies represented by different managers constant. Without rebalancing, assets would be more heavily concentrated in the strategies that worked best in the past. If market conditions then change, the largest asset allocations would be in the strategies that are most vulnerable. In effect, rebalancing helps mitigate the negative impact of the inevitable shifts in market conditions, which can result in being overweight, an outperforming strategy when that strategy has run its course and is about to turn negative; and being underweight, a strategy that is about to have a huge run.


pages: 669 words: 210,153

Tools of Titans: The Tactics, Routines, and Habits of Billionaires, Icons, and World-Class Performers by Timothy Ferriss

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Airbnb, Alexander Shulgin, artificial general intelligence, asset allocation, Atul Gawande, augmented reality, back-to-the-land, Bernie Madoff, Bertrand Russell: In Praise of Idleness, Black Swan, blue-collar work, Buckminster Fuller, business process, Cal Newport, call centre, Checklist Manifesto, cognitive bias, cognitive dissonance, Colonization of Mars, Columbine, commoditize, correlation does not imply causation, David Brooks, David Graeber, diversification, diversified portfolio, Donald Trump, effective altruism, Elon Musk, fault tolerance, fear of failure, Firefox, follow your passion, future of work, Google X / Alphabet X, Howard Zinn, Hugh Fearnley-Whittingstall, Jeff Bezos, job satisfaction, Johann Wolfgang von Goethe, John Markoff, Kevin Kelly, Kickstarter, Lao Tzu, life extension, lifelogging, Mahatma Gandhi, Marc Andreessen, Mark Zuckerberg, Mason jar, Menlo Park, Mikhail Gorbachev, Nicholas Carr, optical character recognition, PageRank, passive income, pattern recognition, Paul Graham, peer-to-peer, Peter H. Diamandis: Planetary Resources, Peter Singer: altruism, Peter Thiel, phenotype, PIHKAL and TIHKAL, post scarcity, premature optimization, QWERTY keyboard, Ralph Waldo Emerson, Ray Kurzweil, recommendation engine, rent-seeking, Richard Feynman, Richard Feynman, risk tolerance, Ronald Reagan, selection bias, sharing economy, side project, Silicon Valley, skunkworks, Skype, Snapchat, social graph, software as a service, software is eating the world, stem cell, Stephen Hawking, Steve Jobs, Stewart Brand, superintelligent machines, Tesla Model S, The Wisdom of Crowds, Thomas L Friedman, Wall-E, Washington Consensus, Whole Earth Catalog, Y Combinator, zero-sum game

and because you ask a question continuously and you believe [there’s an] answer, you get it.” TF: Here’s a wild example. Kyle Bass at one point bought $1 million worth of nickels (roughly 20 million coins). Why? Because their face value was 5 cents and their scrap metal value was 6.8 cents at the time. That’s an immediate gain of $360,000. Nicely done. Asset allocation: “They absolutely, beyond a shadow of a doubt, know they’re going to be wrong . . . so they set up an asset allocation system that will make them successful. They all agree asset allocation is the single most important investment decision.” In Money: Master the Game, Ray Dalio elaborated for Tony: “When people think they’ve got a balanced portfolio, stocks are three times more volatile than bonds. So when you’re 50/50, you’re really 90/10. You really are massively at risk, and that’s why when the markets go down, you get eaten alive. . . .


pages: 586 words: 159,901

Wall Street: How It Works And for Whom by Doug Henwood

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accounting loophole / creative accounting, activist fund / activist shareholder / activist investor, affirmative action, Andrei Shleifer, asset allocation, asset-backed security, bank run, banking crisis, barriers to entry, borderless world, Bretton Woods, British Empire, capital asset pricing model, capital controls, central bank independence, computerized trading, corporate governance, corporate raider, correlation coefficient, correlation does not imply causation, credit crunch, currency manipulation / currency intervention, David Ricardo: comparative advantage, debt deflation, declining real wages, deindustrialization, dematerialisation, diversification, diversified portfolio, Donald Trump, equity premium, Eugene Fama: efficient market hypothesis, experimental subject, facts on the ground, financial deregulation, financial innovation, Financial Instability Hypothesis, floating exchange rates, full employment, George Akerlof, George Gilder, hiring and firing, Hyman Minsky, implied volatility, index arbitrage, index fund, information asymmetry, interest rate swap, Internet Archive, invisible hand, Irwin Jacobs, Isaac Newton, joint-stock company, Joseph Schumpeter, kremlinology, labor-force participation, late capitalism, law of one price, liberal capitalism, liquidationism / Banker’s doctrine / the Treasury view, London Interbank Offered Rate, Louis Bachelier, market bubble, Mexican peso crisis / tequila crisis, microcredit, minimum wage unemployment, money market fund, moral hazard, mortgage debt, mortgage tax deduction, Myron Scholes, oil shock, Paul Samuelson, payday loans, pension reform, Plutocrats, plutocrats, price mechanism, price stability, prisoner's dilemma, profit maximization, publication bias, Ralph Nader, random walk, reserve currency, Richard Thaler, risk tolerance, Robert Gordon, Robert Shiller, Robert Shiller, selection bias, shareholder value, short selling, Slavoj Žižek, South Sea Bubble, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, The Market for Lemons, The Nature of the Firm, The Predators' Ball, The Wealth of Nations by Adam Smith, transaction costs, transcontinental railway, women in the workforce, yield curve, zero-coupon bond

It is interesting, though, that Chen's data shows that the real economy can also be thought of as predicting the stock market (with real weakness portending financial strength), turning the conventional notion of the stock market as the leader WALL STREET and the real world as the follower on its head. When things move in opposite directions, it's admittedly hard to say which is the cause and which is the effect. allocation A good deal of Wall Street time is devoted to asset allocation — figuring out where to put money. Analysts are deployed, both on the buy (customer) and sell (broker) sides, to scrutinize the health of the national economies, industrial sectors, and classes of assets. Though lots of institutional investors are restricted in what they can buy — managers of high-tech mutual funds can't buy auto stocks, and insurance companies don't buy penny stocks — even the most tightly specified have to figure out just what to buy, sell, and hold.

Wall Street firms also deposited their clients' funds with hotshot thrifts, who would then turn around and buy the (often dubious) securities the firms were peddling (Mayer 1990, pp. 296-297). Of course, the U.S. Treasury ultimately picked up the tab for this exercise in market efficiency. 36. Lewis 1989b, p. 31. 37. Figures from Federal Reserve's flow of funds statistics. 38. Greenspan explained that these freelancers pounced when they perceived "subopti-mal asset allocations" (Greenspan 1989, p. 268; Jaroslovsky 1989). 39- Lexecon's argument is also damaged by Michael Barclay's (1996) findings that Nasdaq stocks with wide bid-ask spreads that subsequently shifted to the NYSE showed significant declines in the spread on exchange listing. 40. Several calls to Bennett asking for an interview went unreturned. Renegades In a better world, talk of noise, fads, imperfect knowledge, and emotional overreaction would have traveled beyond the arena of financial economics to the realm where political judgments are made.


pages: 374 words: 114,600

The Quants by Scott Patterson

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Albert Einstein, asset allocation, automated trading system, beat the dealer, Benoit Mandelbrot, Bernie Madoff, Bernie Sanders, Black Swan, Black-Scholes formula, Bonfire of the Vanities, Brownian motion, buttonwood tree, 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, 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, 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

Over a sultry August weekend, Wall Street’s legions of traders, bankers, and hedge fund titans tried to relax, hopping in their Bentleys and BMWs, their Maseratis and Mercedeses, and retreating to the soft sands of the Hamptons beaches or jetting away for quick escapes to anywhere but New York City or Greenwich. They knew trouble was coming. It struck Monday with the force of a sledgehammer. Cliff Asness walked to the glass partition of his corner office and frowned at the rows of cubicles that made up AQR’s Global Asset Allocation group. GAA was replete with hotshot traders and researchers who scoured the globe in search of quantitative riches in everything from commodity futures to currency derivatives. On the other side of the building, separated by a wall that ran down the middle of the office, AQR’s Global Stock Selection team labored away. A job at GSS could be rough. It involved the grunt work of combing through reams of data about stock returns and the grueling task of hoping to find some pattern that the thousands of other Fama-bred quants hadn’t found yet.

Instead, many believed the goal should be to design better bridges—or, in the case of the quants, better, more robust models that could withstand financial tsunamis, not create them. There were some promising signs. Increasingly, firms were adapting models that incorporated the wild, fat-tailed swings described by Mandelbrot decades earlier. J. P. Morgan, the creator of the bell curve–based VAR risk model, was pushing a new asset-allocation model incorporating fat-tailed distributions. Morningstar, a Chicago investment-research group, was offering retirement-plan participants portfolio forecasts based on fat-tailed assumptions. A team of quants at MSCI BARRA, Peter Muller’s old company, had developed a cutting-edge risk-management strategy that accounted for potential black swans. Meanwhile, the markets continued to behave strangely.


pages: 289 words: 113,211

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

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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

In terms of risk management, rather than simply measuring the portfolio’s current risk level—a trivial exercise for equity portfolios—the analysis tries to determine the link between risk and sizing: that is, how good the manager is at modulating risk—pushing leverage and position size up and down—in response to market conditions and trading success. Scribe Reports also proved valuable for helping make asset allocation and hire/fire decisions for investors, funds of funds, and those within a hedge fund who were overseeing the stable of managers. The problem with hedge funds is that they are deliberately opaque. They don’t want anyone to know their positions, lest others trade against them or emulate their strategies. So an investor’s information about a hedge fund is typically limited to monthly performance results and occasional PowerPoint presentations from the manager or investor relations types.

It is clear from a risk management perspective that hedge fund classification provides no unification, hardly even a common thread. Not only do hedge funds cover the waterfront of investment strategies, of which the traditional asset management strategies are only a small part, but those executed by hedge funds are only one point on the spectrum of a surprisingly broad realm of business endeavor that might be called asset allocation businesses. We have already discussed the shorter-term role of the hedge fund in providing liquidity to the market; in that capacity the hedge fund manager is acting as a quasi market maker, taking over a function that has traditionally been the domain of the floor trader or the sellside firm, but which, with the speed of communication and transparency of the market micro structure, can now be outsourced.


pages: 505 words: 142,118

A Man for All Markets by Edward O. Thorp

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3Com Palm IPO, Albert Einstein, asset allocation, beat the dealer, Bernie Madoff, Black Swan, Black-Scholes formula, Brownian motion, buy low sell high, carried interest, Chuck Templeton: OpenTable, Claude Shannon: information theory, cognitive dissonance, collateralized debt obligation, compound rate of return, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, Edward Thorp, Erdős number, Eugene Fama: efficient market hypothesis, financial innovation, George Santayana, German hyperinflation, Henri Poincaré, high net worth, High speed trading, index arbitrage, index fund, interest rate swap, invisible hand, Jarndyce and Jarndyce, Jeff Bezos, John Meriwether, John Nash: game theory, Kenneth Arrow, Livingstone, I presume, Long Term Capital Management, Louis Bachelier, margin call, Mason jar, merger arbitrage, Murray Gell-Mann, Myron Scholes, NetJets, Norbert Wiener, passive investing, Paul Erdős, Paul Samuelson, Pluto: dwarf planet, Ponzi scheme, price anchoring, publish or perish, quantitative trading / quantitative finance, race to the bottom, random walk, Renaissance Technologies, RFID, Richard Feynman, Richard Feynman, risk-adjusted returns, Robert Shiller, Robert Shiller, rolodex, Sharpe ratio, short selling, Silicon Valley, statistical arbitrage, stem cell, survivorship bias, The Myth of the Rational Market, The Predators' Ball, the rule of 72, The Wisdom of Crowds, too big to fail, Upton Sinclair, value at risk, Vanguard fund, Vilfredo Pareto, Works Progress Administration

Zucker, adapted for ebook Cover design: Pete Garceau Cover photograph: © Leigh Wiener v4.1 ep Contents Cover Title Page Copyright Preface Foreword Chapter 1: Loving to Learn Chapter 2: Science Is My Playground Chapter 3: Physics and Mathematics Chapter 4: Las Vegas Chapter 5: Conquering Blackjack Chapter 6: The Day of the Lamb Chapter 7: Card Counting for Everyone Chapter 8: Players Versus Casinos Chapter 9: A Computer That Predicts Roulette Chapter 10: An Edge at Other Gambling Games Chapter 11: Wall Street: The Greatest Casino on Earth Chapter 12: Bridge with Buffett Chapter 13: Going into Partnership Chapter 14: Front-Running the Quantitative Revolution Chapter 15: Rise… Chapter 16: …And Fall Chapter 17: Period of Adjustment Chapter 18: Swindles and Hazards Chapter 19: Buying Low, Selling High Chapter 20: Backing the Truck Up to the Banks Chapter 21: One Last Puff Chapter 22: Hedging Your Bets Chapter 23: How Rich Is Rich? Chapter 24: Compound Growth: The Eighth Wonder of the World Chapter 25: Beat Most Investors by Indexing Chapter 26: Can You Beat the Market? Should You Try? Chapter 27: Asset Allocation and Wealth Management Chapter 28: Giving Back Chapter 29: Financial Crises: Lessons Not Learned Chapter 30: Thoughts Epilogue Appendix A: The Impact of Inflation on the Dollar Appendix B: Historical Returns Appendix C: The Rule of 72 and More Appendix D: Performance of Princeton Newport Partners, LP Appendix E: Our Statistical Arbitrage Results for a Fortune 100 Company Photo Insert Dedication Acknowledgments Notes Bibliography By Edward O.

Be aware that information flows down a “food chain,” with those who get it first “eating” and those who get it late being eaten. Finally, don’t bet on an investment unless you can demonstrate by logic, and if appropriate by track record, that you have an edge. Whether or not you try to beat the market, you can do better by properly managing your wealth, which I talk about next. Chapter 27 * * * ASSET ALLOCATION AND WEALTH MANAGEMENT Private wealth in the industrially advanced countries is spread among major asset classes such as equities (common stocks), bonds, real estate, collectibles, commodities, and miscellaneous personal property. If investors choose index funds for each asset class in which they wish to invest, their combined portfolio risk and return will depend on how they allocate among asset classes.

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

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algorithmic trading, asset allocation, automated trading system, backtesting, Black Swan, Brownian motion, business continuity plan, 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

So if the two hypothetical portfolios have the same average return, then we would prefer the one that has the smaller risk or standard deviation. Empirical studies have found that a portfolio that consists of low-beta stocks generally has lower risk and thus a higher Sharpe ratio. For example, in a paper titled “Risk Parity Portfolios” (not publicly distributed), Dr. Edward Qian at PanAgora Asset Management argued that a typical 60–40 asset allocation between stocks and bonds is not optimal because it is overweighted with risky assets (stocks in this case). Instead, to achieve a higher Sharpe ratio while maintaining the same risk level as the 60–40 portfolio, Dr. Qian recommended a 23–77 allocation while leveraging the entire portfolio by 1.8. Somehow, the market is chronically underpricing high-beta stocks. Hence, given a choice between a portfolio of high-beta stocks and a portfolio of low-beta stocks, we should prefer the lowbeta one, which we can then leverage up to achieve the maximum compounded growth rate.


pages: 186 words: 49,251

The Automatic Customer: Creating a Subscription Business in Any Industry by John Warrillow

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Airbnb, airport security, Amazon Web Services, asset allocation, barriers to entry, call centre, cloud computing, commoditize, David Heinemeier Hansson, discounted cash flows, high net worth, Jeff Bezos, Network effects, passive income, rolodex, sharing economy, side project, Silicon Valley, Silicon Valley startup, software as a service, statistical model, Steve Jobs, Stewart Brand, subscription business, telemarketer, time value of money, zero-sum game, Zipcar

Russell, Mark, “Private Clubs Cut Fees as Golfers Find Less Time for Tee,” Sunday Age, January 17, 2010. newsstore.fairfax.com.au/apps/viewDocument.ac;jsessionid=EDEC72100CFB2E466A2A2353EE4EE47Fsy=afr&pb=all_ffx&dt=selectRange&dr=1month&so=relevance&sf=text&sf=headline&rc=10&rm=200&sp=brs&cls=19059&clsPage=1&docID=SAG100117MG3BA5GE1R9. 2. Sullivan, Paul, “Financial Advice Gleaned from a Day in the Hot Seat,” New York Times, June 17, 2011. nytimes.com/2011/06/18/your-money/asset-allocation/18wealth.html. CHAPTER 6: THE FRONT-OF-THE LINE MODEL 1. “Premier Success Plans,” Salesforce.com, last modified March 12, 2014. www2.sfdcstatic.com/assets/pdf/datasheets/DS_SuccessPlans.pdf. 2. “Mission Critical Success,” Salesforce.com, last modified July 7, 2013. www2.sfdcstatic.com/assets/pdf/datasheets/MCS_Datasheet.pdf. CHAPTER 7: THE CONSUMABLES MODEL 1. Dahl, Darren, “Riding the Momentum Created by a Cheeky Video,” New York Times, April 10, 2013. nytimes.com/2013/04/11/business/smallbusiness/dollar-shave-club-from-viral-video-to-real-business.html. 2.


pages: 271 words: 52,814

Blockchain: Blueprint for a New Economy by Melanie Swan

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23andMe, Airbnb, altcoin, Amazon Web Services, asset allocation, banking crisis, basic income, bioinformatics, bitcoin, blockchain, capital controls, cellular automata, central bank independence, clean water, cloud computing, collaborative editing, Conway's Game of Life, crowdsourcing, cryptocurrency, disintermediation, Edward Snowden, en.wikipedia.org, ethereum blockchain, fault tolerance, fiat currency, financial innovation, Firefox, friendly AI, Hernando de Soto, intangible asset, Internet Archive, Internet of things, Khan Academy, Kickstarter, lifelogging, litecoin, Lyft, M-Pesa, microbiome, Network effects, new economy, peer-to-peer, peer-to-peer lending, peer-to-peer model, personalized medicine, post scarcity, prediction markets, QR code, ride hailing / ride sharing, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, SETI@home, sharing economy, Skype, smart cities, smart contracts, smart grid, software as a service, technological singularity, Turing complete, unbanked and underbanked, underbanked, web application, WikiLeaks

In the cryptocurrency sense, demurrage can mean being deflationary (value losing) over time, thus incitory (stimulatory) in that it incites some form of action taking (i.e.; spending) in the shorter term to realize value before it is lost. The currency itself thus encourages economic activity. Demurrage, then, is the compact concept of an attribute, the idea of an automatic motivating or incitory property being built in to something. Further, another aspect of demurrage currencies (or really all digital network–based asset allocation, tracking, interaction, and transaction structures) is the notion of periodic automatic redistribution of the currency (the resource) across all network nodes at certain prespecified times, or in the case of certain events. Demurrage features could become a powerful and standard currency administration tool. Freicoin and Healthcoin are two examples of uses of a demurrage currency with a built-in mechanism for action taking in the form of spending.


Design of Business: Why Design Thinking Is the Next Competitive Advantage by Roger L. Martin

asset allocation, Buckminster Fuller, business process, Frank Gehry, global supply chain, high net worth, Innovator's Dilemma, Isaac Newton, mobile money, QWERTY keyboard, Ralph Waldo Emerson, risk tolerance, six sigma, Steve Ballmer, Steve Jobs, supply-chain management, Wall-E, winner-take-all economy

It is little consolation that the formula is bias-free. The Pressures of Time The third reason that reliability tends to trump validity in business settings is, quite simply, time. A reliable system can generate tremendous time savings; once designed, it eliminates the need for subjective and thoughtful analysis by an expensive and time-pressed manager or professional. Hence the appeal of automated asset-allocation systems at investment advisory firms: before new clients even meet an adviser, the clients complete a questionnaire designed to reliably assess their investment horizons, risk tolerance, and investment goals. The data feeds into a program that impersonally graphs the recommended mix of stocks, bonds, and other investments. It takes the massively complex job of understanding individual investment needs out of the hands of the adviser.


pages: 222 words: 50,318

The Option of Urbanism: Investing in a New American Dream by Christopher B. Leinberger

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American Society of Civil Engineers: Report Card, asset allocation, big-box store, centre right, commoditize, credit crunch, David Brooks, desegregation, Donald Trump, drive until you qualify, edge city, full employment, Intergovernmental Panel on Climate Change (IPCC), Jane Jacobs, knowledge economy, McMansion, mortgage tax deduction, new economy, New Urbanism, peak oil, Ponzi scheme, postindustrial economy, RAND corporation, Report Card for America’s Infrastructure, reserve currency, Richard Florida, Seaside, Florida, the built environment, transit-oriented development, urban planning, urban renewal, urban sprawl, walkable city, white flight

Nearly 50 million new homes will be built, including some 16 million that will be rebuilt or replaced entirely with other land uses. Seventy-five billion square feet of nonresidential space will be built with 60 billion [square feet] replacing space that existed in 2000: New nonresidential development will equal all such development that existed in 2000.”23 This is a tremendous amount of development that, if it follows current asset allocation, will require around thirty-five percent of American investment capital during that period. This would be the largest portion the country will invest in any asset class—more than government and corporate research and development, more than all of the capital investment in publicly traded companies, and more than the country’s defense spending. Yet this change will take longer to implement than, for example, completely replacing the fleet of cars and trucks on the roads today.


pages: 300 words: 79,315

Getting Things Done: The Art of Stress-Free Productivity by David Allen

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Albert Einstein, asset allocation, cognitive dissonance, conceptual framework, Everything should be made as simple as possible, George Santayana, index card, knowledge worker, Ralph Waldo Emerson, rolodex

The addition of brainstorming—the most creative means of expressing and capturing ideas, perspectives, and details about projects—makes for an elegant set of behaviors for staying relaxed and getting things done. Shifting to a Positive Organizational Culture It doesn’t take a big change to increase the productivity standards of a group. I continually get feedback indicating that with a little implementation, this method immediately makes things happen more quickly and more easily. The constructive evaluation of activities, asset allocations, communications, policies, and procedures against purposes and intended outcomes has become increasingly critical for every organization I know of. The challenges to our companies continue to mount, with pressures coming these days from globalization, competition, technology, shifting markets, and raised standards of performance and production. “What do we want to have happen in this meeting?”


pages: 189 words: 64,571

The Cheapskate Next Door: The Surprising Secrets of Americans Living Happily Below Their Means by Jeff Yeager

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asset allocation, carbon footprint, delayed gratification, dumpster diving, index card, job satisfaction, late fees, mortgage debt, new economy, payday loans, Skype, upwardly mobile, Zipcar

Of cheapskate portfolios I was made privy to, the key characteristics were these: Diversification with a large percentage of bonds and other lending investments, and a smaller share of equities than is typically promoted in the financial media. Minimizing fees, particularly by investing in index mutual funds or “exchange-traded funds,” which are so-called “baskets”of related securities designed to track existing indexes like the S&P 500. Rebalancing investments periodically, according to an asset allocation plan. Dollar-cost averaging, or, in other words, continually investing on a regular schedule to even out fluctuations in the markets. Remembering that “pigs get fat, hogs get slaughtered” (as one cheapskate put it). Cheapskates don’t get too greedy or aggressive, because it’s only money, and the cheapskate next door doesn’t need that much of it to be truly happy. The Cheapskate’s Take on Credit and Debt The cheapskate’s credit history is, by today’s standards, not much of a history at all.


pages: 263 words: 75,455

Quantitative Value: A Practitioner's Guide to Automating Intelligent Investment and Eliminating Behavioral Errors by Wesley R. Gray, Tobias E. Carlisle

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activist fund / activist shareholder / activist investor, Albert Einstein, Andrei Shleifer, asset allocation, Atul Gawande, backtesting, beat the dealer, Black Swan, capital asset pricing model, Checklist Manifesto, cognitive bias, compound rate of return, corporate governance, correlation coefficient, credit crunch, Daniel Kahneman / Amos Tversky, discounted cash flows, Edward Thorp, Eugene Fama: efficient market hypothesis, forensic accounting, hindsight bias, intangible asset, Louis Bachelier, p-value, passive investing, performance metric, quantitative hedge fund, random walk, Richard Thaler, risk-adjusted returns, Robert Shiller, Robert Shiller, shareholder value, Sharpe ratio, short selling, statistical model, survivorship bias, systematic trading, The Myth of the Rational Market, time value of money, transaction costs

He is a graduate of the University of Queensland in Australia with degrees in law and business (management). About the Companion Website This book includes a companion website, which can be found at www.wiley.com/go/quantvalue. This website includes: A screening tool to find stocks using the model in the book. A tool designed to facilitate the implementation for a variety of tactical asset allocation models. A back-testing tool that allows users to compare performance among competing investment strategies. A blog about recent developments in quantitative value investing. Index Accruals detecting earnings manipulation Activism and cloning Adjustment bias Alpha and adjusted performance sustainable Altman, Edward I. Analysis legend Anchoring Anderson, Keith Apple Inc. Availability bias Ayres, Ian Bachelier, Louis Bailey, Morris Bankruptcy prediction history of improving Batchelor, Roy Beat the Dealer (Thorp) Beat the Market: A Scientific Stock Market System (Thorp & Kassouf) Behavioral errors, quantitative investing's protection against cognitive biases experts' errors value investors'errors Behavioral Investing: A Practitioners Guide to Applying Behavioral Finance (Montier) Benchmarking Beneish, Messod Berk, Jonathan Bogue, Marcus Bonaime, Alice Book value-to-market capitalization ratio Brooks, Chris Buffett, Warren See's Candies acquisition Buybacks Campbell, John Cash flow on assets (CFOA) CGM Focus Fund Chava, Sudheer “The Checklist” (Gawande) The Checklist Manifesto: How to Get Things Right (Gawande) Chuvakhin, Nikolai Cloning Cognitive biases adjustment bias anchoring availability bias hindsight bias neglect of the base case overconfidence self-attribution bias Confirmation bias “Contrarian Investment, Extrapolation, and Risk” (Lakonishok, Schleifer, & Vishny) Cowles, Alfred, III “The Cross-Section of Expected Stock Returns” (Fama & French) Data mining “Decoding Inside Information” (Cohen, Malloy, & Pomorski) “Delisting Returns and Their Effect on Accounting-Based Market Anomalies” (Price, Beaver, & McNichols) Dumb money, paradox of behavioral errors, quantitative investing's protection against cognitive biases experts' errors value investors'errors quantitative value investing, power of value strategies Graham's quantitative Earnings manipulators and frauds, eliminating accruals detecting earnings manipulation PROBMs, predicting Enron Earnings yield Efficient market theory Einhorn, David Enron Enterprise yield (EBITDA and EBIT variations) Expert Political Judgment (Tetlock) Fama, Eugene Financial distress, measuring risk of bankruptcy prediction history of improving calculating universe, scrubbing Financial strength case study: Lubrizol Corporation comparing performance of F_SCORE and FS_SCORE financial strength score (FS_SCORE) current profitability formula and interpretation recent operational improvements stability Piotroski Fundamental Score (F_SCORE) analyzing formula and interpretation Fooled by Randomness (Taleb) Forward earnings estimate Franchises finding economic moats and excess returns persistence pricing power and big, stable margins See's Candies, acquisition by Buffett Fraud.


pages: 237 words: 64,411

Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence by Jerry Kaplan

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Affordable Care Act / Obamacare, Amazon Web Services, asset allocation, autonomous vehicles, bank run, bitcoin, Bob Noyce, Brian Krebs, buy low sell high, Capital in the Twenty-First Century by Thomas Piketty, combinatorial explosion, computer vision, corporate governance, crowdsourcing, en.wikipedia.org, Erik Brynjolfsson, estate planning, Flash crash, Gini coefficient, Goldman Sachs: Vampire Squid, haute couture, hiring and firing, income inequality, index card, industrial robot, information asymmetry, invention of agriculture, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, Loebner Prize, Mark Zuckerberg, mortgage debt, natural language processing, Own Your Own Home, pattern recognition, Satoshi Nakamoto, school choice, Schrödinger's Cat, Second Machine Age, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley startup, Skype, software as a service, The Chicago School, The Future of Employment, Turing test, Watson beat the top human players on Jeopardy!, winner-take-all economy, women in the workforce, working poor, Works Progress Administration

We don’t need to take from the wealthy and give to the less fortunate because our economy is not standing still; it’s continually expanding, and this growth is likely to quicken. So all we need to do is distribute the benefits of future growth more widely, and the problem will slowly melt away. A carefully crafted program of tax incentives, portfolio transparency, and increased individual control over asset allocation based on the PBI offers us a way to keep from capsizing in the rising tide of concentrating prosperity. So why can’t our chosen leaders better assess the situation and take corrective actions? Because you can’t steer when you can’t see, and you can’t discuss what you can’t articulate. At the moment, our public discourse lacks the concepts and exemplars to properly describe what’s likely to happen as technological progress accelerates, much less to guide us to reasonable solutions.


pages: 233 words: 71,342

Straight Flush: The True Story of Six College Friends Who Dealt Their Way to a Billion-Dollar Online Poker Empire--And How It All Came Crashing Down... by Ben Mezrich

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asset allocation, call centre, urban sprawl

In between, they’d be staying in a hotel just around the corner, a disgusting little place Hilt had found on the Internet that offered tiny un-air-conditioned rooms teeming with cockroaches—because every penny they had would be going into that check. Hilt paused at the door, giving Scott a chance to fix his tie one last time. Then he led the way inside. I have to admit, this all looks pretty good.” Hilt was leaning forward in the seat next to Scott, at the edge of the mahogany desk, poking through the huge stack of papers in front of them. Balance sheets, financial statements, asset allocations—all of it printed out at their request by the bank manager, who had now stepped outside to give them time to look through things in private. Even more important than the papers, to Scott, was the manager himself; Scott hadn’t been able to stifle his surprise when he first stepped foot into the island bank and caught sight of the well-dressed, midfifties American, with his neatly combed silver hair, traditional-looking wire-rimmed glasses, and impeccable gray suit.


pages: 294 words: 82,438

Simple Rules: How to Thrive in a Complex World by Donald Sull, Kathleen M. Eisenhardt

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Affordable Care Act / Obamacare, Airbnb, asset allocation, Atul Gawande, barriers to entry, Basel III, Berlin Wall, carbon footprint, Checklist Manifesto, complexity theory, Craig Reynolds: boids flock, Credit Default Swap, Daniel Kahneman / Amos Tversky, diversification, drone strike, en.wikipedia.org, European colonialism, Exxon Valdez, facts on the ground, Fall of the Berlin Wall, haute cuisine, invention of the printing press, Isaac Newton, Kickstarter, late fees, Lean Startup, Louis Pasteur, Lyft, Moneyball by Michael Lewis explains big data, Nate Silver, Network effects, obamacare, Paul Graham, performance metric, price anchoring, RAND corporation, risk/return, Saturday Night Live, sharing economy, Silicon Valley, Startup school, statistical model, Steve Jobs, TaskRabbit, The Signal and the Noise by Nate Silver, transportation-network company, two-sided market, Wall-E, web application, Y Combinator, Zipcar

. [>] A study of personal: Grant Richardson, “Determinants of Tax Evasion: A Cross-Country Investigation,” Journal of International Accounting, Auditing, and Taxation 15, no. 2 (2006): 150–69. [>] According to the: “Retirement Savings Assessment 2013,” Fidelity, accessed January 23, 2014, http://www.fidelity.com/inside-fidelity/individual-investing/fidelity-unveils-new-retirement-preparednessmeasure. [>] When employers offered: Sheena S. Iyengar and Emir Kamenica, “Choice Proliferation, Simplicity Seeking, and Asset Allocation,” Journal of Public Economics 94, no. 7–8 (2010): 530–39. For a broader review of the related literature, see Roy Yong-Joo Chua and Sheena S. Iyengar, “Empowerment Through Choice? A Critical Analysis of the Effects of Choice in Organizations,” Research in Organizational Behavior 27 (2006): 41–79. [>] Overwhelmed by complexity: The perceived complexity of a choice is influenced not only by the number of options, but also by other factors including how the options are categorized, the number of attributes per option, and ease of comparison across options.

Mastering Book-Keeping: A Complete Guide to the Principles and Practice of Business Accounting by Peter Marshall

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accounting loophole / creative accounting, asset allocation, double entry bookkeeping, information retrieval, intangible asset, the market place

Figures 91 to 96 provide an illustration of the accounting for all these items in the final accounts. 144 56 Balance sheets of limited companies No ledger posting needed The balance sheet is not a ledger account, so there is no ledger posting to do. We simply draw up a statement showing the balances left on the ledger after we have compiled the trading, profit and loss account. Using the trial balance on page 140 we will compile a balance sheet for internal use, that also meets the requirements of the Companies Act 1985 (Format 1). Compiling a company balance sheet step by step 1. Make a heading: ‘Fixed assets’. Allocate three cash columns on the right of a sheet of paper, and head them ‘Cost’, ‘Less provision for depreciation’, and ‘Net book value’. Underneath, record the values for each fixed asset. Net book value means value after depreciation. On the left write against each the name of the asset concerned. Total up each column and cross cast (cross check). 2. Make a heading: ‘Current assets’. Enter in the second column the value of stock then write against it on the left: ‘Stock’.


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, light touch regulation, London Interbank Offered Rate, London Whale, mortgage debt, Northern Rock, performance metric, Ponzi scheme, Ronald Reagan, sovereign wealth fund, urban sprawl

The Journal identified several institutions whose Libor submissions looked particularly out of whack with the cost of insuring their debt, including Citigroup and UBS. The same day, a senior Barclays banker in England broke ranks during a televised interview with Bloomberg and admitted his bank had felt forced into lowballing its submissions. “We had one week in September where our treasurer, who takes his responsibilities pretty seriously, said: ‘Right, I’ve had enough of this, I’m going to quote the right rates,”’ said Tim Bond, head of asset-allocation research at Barclays at the time. “All we got for our pains was a series of media articles saying that we were having difficulty financing.” Anything With Four Legs 47 Bond was referring to the first week of September 2007, when Bloomberg published a column asking: “So what the hell is happening at Barclays and its Barclays Capital securities unit that is prompting its peers to charge it premium interest rates in the money market?”

Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals by David Aronson

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Albert Einstein, Andrew Wiles, asset allocation, availability heuristic, backtesting, Black Swan, capital asset pricing model, cognitive dissonance, compound rate of return, computerized trading, Daniel Kahneman / Amos Tversky, distributed generation, Elliott wave, en.wikipedia.org, feminist movement, hindsight bias, index fund, invention of the telescope, invisible hand, Long Term Capital Management, mental accounting, meta analysis, meta-analysis, p-value, pattern recognition, Paul Samuelson, Ponzi scheme, price anchoring, price stability, quantitative trading / quantitative finance, Ralph Nelson Elliott, random walk, retrograde motion, revision control, risk tolerance, risk-adjusted returns, riskless arbitrage, Robert Shiller, Robert Shiller, Sharpe ratio, short selling, source of truth, statistical model, systematic trading, the scientific method, transfer pricing, unbiased observer, yield curve, Yogi Berra

Outside of academia, there has been a move to greater emphasis on objective methods of TA, but often the results are not evaluated in a statistically rigorous manner. 17. F.D. Arditti, “Can Analysts Distinguish Between Real and Randomly Generated Stock Prices?,” Financial Analysts Journal 34, no. 6 (November/ December 1978), 70. 18. J.J. Siegel, Stocks for the Long Run, 2nd ed. (New York: McGraw-Hill, 1998), 243. 19. G.R. Jensen, R.R. Johnson, and J.M. Mercer, “Tactical Asset Allocation and Commodity Futures: Ways to Improve Performance,” Journal of Portfolio Management 28, no. 4 (Summer 2002). 20. C.R. Lightner, “A Rationale for Managed Futures,” Technical Analysis of Stocks & Commodities (2003). Note that this publication is not a peer-reviewed journal but the article appeared to be well supported and its findings were consistent with the peer-reviewed article cited in the prior note. 21.

Grains (corn, soybeans, soybean meal, soybean oil, and wheat); financials (5year T-notes, 10-year T-notes, long-term treasury bonds); currencies (Australian, British, Canadian, German, Swiss, and Japanese); energy (heating oil, natural gas, crude oil, and unleaded gas); cattle; metals (gold, copper, and silver); and soft/tropical (coffee, cotton, and sugar). G.R. Jensen, R.R. Johnson, and J.M. Mercer, “Tactical Asset Allocation and Commodity Futures,” Journal of Portfolio Management 28, no. 4 (Summer 2002). An asset-class benchmark measures the returns earned and risks incurred by investing in a specific asset class, with no management skill. Lars Kestner, Quantitative Trading Strategies: Harnessing the Power of Quantitative Techniques to Create a Winning Trading Program (New York: McGraw-Hill, 2003), 129–180. The eight market sectors tested were foreign exchange, interest rates, stock index, metals, energy, grains, meats, and softs.


pages: 544 words: 168,076

Red Plenty by Francis Spufford

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affirmative action, anti-communist, Anton Chekhov, asset allocation, Buckminster Fuller, clean water, cognitive dissonance, computer age, double helix, Fellow of the Royal Society, John von Neumann, Kitchen Debate, linear programming, market clearing, New Journalism, oil shock, Philip Mirowski, Plutocrats, plutocrats, profit motive, RAND corporation, Simon Kuznets, the scientific method

Soviet economists tended to be aware of pre-Marxian classical economics, at least in the form of citations and summaries, but not the post-Marxian development of it. The ‘marginalist revolution’ of the late nineteenth century was little known, and with it the characteristic mathematical formalisations of Western economics. Those who were well-enough informed to know about the ‘socialist calculation debate’ (see below, introduction to part II) were conscious that their proposals for optimal asset allocation presupposed a Walrasian model of general equilibrium, but Pareto was reputed only as a quasi-fascist, and Keynes as one more ‘bourgeois apologist’, whose fancy footwork could not disguise the unchanging operations of capital, as diagnosed once and for ever by Marx. For Marx’s formulation of the labour theory, see Freedman, ed., Marx on Economics, pp. 27–63; Leszek Kolakowski, Main Currents of Marxism: The Founders, the Golden Age, the Breakdown, translated from the Polish by P.S.Falla, one-volume edition (New York: W.W.Norton, 2005), pp. 219–26.

Soviet economists tended to be aware of pre-Marxian classical economics, at least in the form of citations and summaries, but not the post-Marxian development of it. The ‘marginalist revolution’ of the late nineteenth century was little known, and with it the characteristic mathematical formalisations of Western economics. Those who were well-enough informed to know about the ‘socialist calculation debate’ (see below, introduction to part II) were conscious that their proposals for optimal asset allocation presupposed a Walrasian model of general equilibrium, but Pareto was reputed only as a quasi-fascist, and Keynes as one more ‘bourgeois apologist’, whose fancy footwork could not disguise the unchanging operations of capital, as diagnosed once and for ever by Marx. For Marx’s formulation of the labour theory, see Freedman, ed., Marx on Economics, pp. 27–63; Leszek Kolakowski, Main Currents of Marxism: The Founders, the Golden Age, the Breakdown, translated from the Polish by P.S.Falla, one-volume edition (New York: W.W.Norton, 2005), pp. 219–26.


pages: 695 words: 194,693

Money Changes Everything: How Finance Made Civilization Possible by William N. Goetzmann

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Albert Einstein, Andrei Shleifer, asset allocation, asset-backed security, banking crisis, Benoit Mandelbrot, Black Swan, Black-Scholes formula, Bretton Woods, Brownian motion, capital asset pricing model, Cass Sunstein, collective bargaining, colonial exploitation, compound rate of return, conceptual framework, corporate governance, Credit Default Swap, David Ricardo: comparative advantage, debt deflation, delayed gratification, Detroit bankruptcy, disintermediation, diversified portfolio, double entry bookkeeping, Edmond Halley, en.wikipedia.org, equity premium, financial independence, financial innovation, financial intermediation, fixed income, frictionless, frictionless market, full employment, high net worth, income inequality, index fund, invention of the steam engine, invention of writing, invisible hand, James Watt: steam engine, joint-stock company, joint-stock limited liability company, laissez-faire capitalism, Louis Bachelier, mandelbrot fractal, market bubble, means of production, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, Myron Scholes, new economy, passive investing, Paul Lévy, Ponzi scheme, price stability, principal–agent problem, profit maximization, profit motive, quantitative trading / quantitative finance, random walk, Richard Thaler, Robert Shiller, Robert Shiller, shareholder value, short selling, South Sea Bubble, sovereign wealth fund, spice trade, stochastic process, the scientific method, The Wealth of Nations by Adam Smith, Thomas Malthus, time value of money, too big to fail, trade liberalization, trade route, transatlantic slave trade, transatlantic slave trade, tulip mania, wage slave

He and Shlomo Benartzi of the University of California in Los Angeles did a study of investor decisions about pension fund options.5 They found a disappointing pattern. People seemed not to understand the difference between stocks and bonds. They tended to divide their portfolio equally across the choices presented in their 401(k) plans, regardless of whether there were more bond funds or stock funds. The implications of this study and similar experiments testing investor skill at basic asset allocation are that people might not be able to manage their own investments. The future might be better for the average person if someone else decided for them. Walking down this logical path leads to a paternalistic state that disempowers the individual. This is contrary to American values and the early theme of a shareholder democracy. Or could we just push people a little bit in the right direction without taking the decision-making power from them?

See also life annuities Anthony and Cleopatra, 107 antichretic loans, 42 antitrust prosecution: in ancient Athens, 76; US law enabling, 448 antoninianus, 131 Antwerp, Elizabethan merchants in, 308 Apum, 61–63 Arabic mathematics, 238, 240–41 Arabic numerals, 238, 241, 248 Aragonese kings: bailiwicks of, 215; Knights Templar as mercenaries for, 210, 214 Archytas, 94–95 argentarii, 110, 112 Aristotle: on origin of coins, 98–99, 100, 101; on usury, 233 Armstrong, Barbara, 497 Art of War (Sunzi), 160 as (Roman coin), 129, 130 asiento, 334–35, 336, 337, 339 asset allocation: by individual investors, 514–15. See also portfolio optimization asset valuation models: alternative use of capital and, 237; risk premium and, 237 assignats, 391–92, 400 Assur, 60–62 Astana graveyard, 177–78 Athens, ancient: banks of, 81–85, 90, 91; commercial law system of, 80–81; court system of, 17, 73, 75 (see also jurors, Athenian); democracy in, 17, 92, 94, 95, 96, 101, 102; expenditures for ceremonial events in, 84; financial literacy in, 17, 85–86, 91, 94–95; fiscal structure for, 92, 94; grain imported by, 73, 75–76, 91, 102; interest loans in, 41; investments facilitated by bankers of, 84–85, 90; loan contract for merchant voyage from, 77–81; monetization of economy in, 17; money and mental framework in, 95; silver mined by, 87–90; summary of finance in, 17, 90–91, 101–2; tetradrachm coins of, 89, 93, 96–98, 102; trial of grain dealers in, 75–76.


pages: 261 words: 103,244

Economists and the Powerful by Norbert Haring, Norbert H. Ring, Niall Douglas

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accounting loophole / creative accounting, Affordable Care Act / Obamacare, Albert Einstein, asset allocation, bank run, barriers to entry, Basel III, Bernie Madoff, British Empire, central bank independence, collective bargaining, commodity trading advisor, corporate governance, creative destruction, credit crunch, Credit Default Swap, David Ricardo: comparative advantage, diversified portfolio, financial deregulation, George Akerlof, illegal immigration, income inequality, inflation targeting, information asymmetry, Jean Tirole, job satisfaction, Joseph Schumpeter, Kenneth Arrow, knowledge worker, labour market flexibility, law of one price, light touch regulation, Long Term Capital Management, low skilled workers, mandatory minimum, market bubble, market clearing, market fundamentalism, means of production, minimum wage unemployment, moral hazard, new economy, obamacare, old-boy network, open economy, Pareto efficiency, Paul Samuelson, pension reform, Ponzi scheme, price stability, principal–agent problem, profit maximization, purchasing power parity, Renaissance Technologies, rolodex, Sergey Aleynikov, shareholder value, short selling, Steve Jobs, The Chicago School, the payments system, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, ultimatum game, union organizing, Vilfredo Pareto, working-age population, World Values Survey

Until the mid-1970s, the rating agencies were rather modestly sized, modestly influential institutions selling their judgment to investors who subscribed to their service. Then in 1975, the SEC named the three largest ones, Moody’s, Standard & Poor’s and Fitch, as Nationally Recognized Statistical Rating Organizations and made the capital that banks had to hold dependent on these agencies’ judgment of the quality of the securities they owned. Private endowments, foundations and mutual funds also used these ratings in setting asset allocation guidelines for their investment managers. Thus the SEC was in effect giving the agencies a quasi-monopoly to sell a license to issue securities. If they rated a security badly, demand would be very low because banks would have to hold too much capital in reserve for them. Essentially, the opinions 98 ECONOMISTS AND THE POWERFUL of the agencies had attained the force of law. Ironically, the reports of the agencies carry a disclaimer that urges users not to rely on any credit rating in making any investment decision, advice that most investors are required to ignore by law or by statute.


pages: 444 words: 86,565

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

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asset allocation, asset-backed security, bank run, barriers to entry, 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, technology bubble, time value of money, transaction costs, yield curve

For example, the interpolated yield for a 10-year Treasury note can be obtained from Bloomberg by typing “ICUR10,” then pressing <GO>. 91 Located under “Daily Treasury Yield Curve Rates.” 92 The 30-year Treasury bond was discontinued on February 18, 2002, and reintroduced on February 9, 2006. 93 Morningstar acquired Ibbotson Associates in March 2006. Ibbotson Associates is a leading authority on asset allocation, providing products and services to help investment professionals obtain, manage, and retain assets. Morningstar’s annual Ibbotson® SBBI® (Stocks, Bonds, Bills, and Inflation) Valuation Yearbook is a widely used reference for cost of capital input estimations for U.S.-based businesses. 94 Bloomberg function: “ICUR20” <GO>. 95 While there are currently no 20-year Treasury bonds issued by the U.S.


pages: 324 words: 92,805

The Impulse Society: America in the Age of Instant Gratification by Paul Roberts

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2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, accounting loophole / creative accounting, activist fund / activist shareholder / activist investor, Affordable Care Act / Obamacare, American Society of Civil Engineers: Report Card, asset allocation, business process, Cass Sunstein, centre right, choice architecture, collateralized debt obligation, collective bargaining, computerized trading, corporate governance, corporate raider, corporate social responsibility, creative destruction, crony capitalism, David Brooks, delayed gratification, double helix, factory automation, financial deregulation, financial innovation, fixed income, full employment, game design, greed is good, If something cannot go on forever, it will stop - Herbert Stein's Law, impulse control, income inequality, inflation targeting, invisible hand, job automation, John Markoff, Joseph Schumpeter, knowledge worker, late fees, Long Term Capital Management, loss aversion, low skilled workers, mass immigration, new economy, Nicholas Carr, obamacare, Occupy movement, oil shale / tar sands, performance metric, postindustrial economy, profit maximization, Report Card for America’s Infrastructure, reshoring, Richard Thaler, rising living standards, Robert Shiller, Robert Shiller, Rodney Brooks, Ronald Reagan, shareholder value, Silicon Valley, speech recognition, Steve Jobs, technoutopianism, the built environment, The Predators' Ball, the scientific method, The Wealth of Nations by Adam Smith, Thorstein Veblen, too big to fail, total factor productivity, Tyler Cowen: Great Stagnation, Walter Mischel, winner-take-all economy

NPR Staff, “Tired of Inequality One Economist Said It’ll Only Get Worse,” NPR.org, Sept. 12, 2013, http://www.npr.org/2013/09/12/221425582/tired-of-inequality-one-economist-says-itll-only-get-worse. 36. Ibid. 37. Hannah Kuchler, “Data Pioneers Watching Us Work,” Financial Times, February 17, 2014. 38. NPR, “Tired of Inequality.” 39. Paul Sullivan, “Twitter Tantalizes, but Beware the I.P.O.” The New York Times, Oct. 25, 2013, http://www.nytimes.com/2013/10/26/your-money/asset-allocation/twitter-tantalizes-but-beware-the-ipo.htmlhpw. 40. “IPO Performance,” graph, Renaissance Capital IPO Center, http://www.renaissancecapital.com/ipohome/press/mediaroom.aspxmarket=us. 41. Susan Fleck, John Glasser, and Shawn Sprague, “The Compensation-Productivity Gap: A Visual Essay,” Monthly Labor Review (Jan. 2011). 42. Jacob S. Hacker and Paul Pierson, Winner-Take-All Politics: How Washington Made the Rich Richer—and Turned Its Back on the Middle Class (New York: Simon & Schuster, 2011), pp. 3-4. 43.


pages: 347 words: 97,721

Only Humans Need Apply: Winners and Losers in the Age of Smart Machines by Thomas H. Davenport, Julia Kirby

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AI winter, Andy Kessler, artificial general intelligence, asset allocation, Automated Insights, autonomous vehicles, basic income, Baxter: Rethink Robotics, business intelligence, business process, call centre, carbon-based life, Clayton Christensen, clockwork universe, commoditize, conceptual framework, dark matter, David Brooks, deliberate practice, deskilling, digital map, Douglas Engelbart, Edward Lloyd's coffeehouse, Elon Musk, Erik Brynjolfsson, estate planning, fixed income, follow your passion, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, game design, general-purpose programming language, Google Glasses, Hans Lippershey, haute cuisine, income inequality, index fund, industrial robot, information retrieval, intermodal, Internet of things, inventory management, Isaac Newton, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Khan Academy, knowledge worker, labor-force participation, lifelogging, loss aversion, Mark Zuckerberg, Narrative Science, natural language processing, Norbert Wiener, nuclear winter, pattern recognition, performance metric, Peter Thiel, precariat, quantitative trading / quantitative finance, Ray Kurzweil, Richard Feynman, Richard Feynman, risk tolerance, Robert Shiller, Robert Shiller, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, six sigma, Skype, speech recognition, spinning jenny, statistical model, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, superintelligent machines, supply-chain management, transaction costs, Tyler Cowen: Great Stagnation, Watson beat the top human players on Jeopardy!, Works Progress Administration, Zipcar

As global financial environments (interest rates, economic growth, etc.) change, stepping up means saying how automated advice should change with them. At Betterment, for example, one of the larger and more successful startups in the robo-advisor space, there is a “Behavioral Finance and Investing” department made up of five experts focusing on how to improve their system’s investment advice, determining the right asset allocation, changing investment management strategies over time, and “behavioral design”—trying to nudge Betterment customers toward more rational economic behaviors with their investments. Stepping aside to perform tasks that computers don’t do well is a viable prospect for many financial advisors. Grant Easterbrook, who covered financial technology firms as an industry analyst (he’s now moved to a financial technology startup) told us that, while creating an investment portfolio is relatively easy to automate, it still requires a human touch to provide complex financial planning for individuals with substantial assets.


pages: 326 words: 106,053

The Wisdom of Crowds by James Surowiecki

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AltaVista, Andrei Shleifer, asset allocation, Cass Sunstein, Daniel Kahneman / Amos Tversky, experimental economics, Frederick Winslow Taylor, George Akerlof, Howard Rheingold, I think there is a world market for maybe five computers, interchangeable parts, Jeff Bezos, John Meriwether, Joseph Schumpeter, knowledge economy, lone genius, Long Term Capital Management, market bubble, market clearing, market design, moral hazard, Myron Scholes, new economy, offshore financial centre, Picturephone, prediction markets, profit maximization, Richard Feynman, Richard Feynman, Richard Feynman: Challenger O-ring, Richard Thaler, Robert Shiller, Robert Shiller, Ronald Coase, Ronald Reagan, shareholder value, short selling, Silicon Valley, South Sea Bubble, The Nature of the Firm, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Toyota Production System, transaction costs, ultimatum game, Yogi Berra, zero-sum game

The problem is that it’s hard for mutual-fund investors to know if their money manager is, in fact, investing their money wisely. After all, if you knew what investing wisely was, you’d do it yourself. Obviously you can look at performance, but we know that short-term performance is an imperfect indicator of skill at best. In any one quarter, a manager’s performance may be significantly better or worse depending on factors that have absolutely nothing to do with his stock-picking or asset-allocation skills. So investors need more evidence that a mutual-fund manager’s decisions are reasonable. The answer? Look at how a manager’s style compares to that of his peers. If he’s following the same strategy—investing in the same kinds of stocks, allocating money to the same kinds of assets—then at least investors know he’s not irrational. The problem, of course, is that this means that, all other things being equal, someone who bucks the crowd—by, say, following a contrarian strategy—is likely to be considered crazy.


pages: 293 words: 88,490

The End of Theory: Financial Crises, the Failure of Economics, and the Sweep of Human Interaction by Richard Bookstaber

asset allocation, bank run, bitcoin, butterfly effect, capital asset pricing model, cellular automata, collateralized debt obligation, conceptual framework, constrained optimization, Craig Reynolds: boids flock, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, dark matter, disintermediation, Edward Lorenz: Chaos theory, epigenetics, feminist movement, financial innovation, fixed income, Flash crash, Henri Poincaré, information asymmetry, invisible hand, Isaac Newton, John Conway, John Meriwether, John von Neumann, Joseph Schumpeter, Long Term Capital Management, margin call, market clearing, market microstructure, money market fund, Paul Samuelson, Pierre-Simon Laplace, Piper Alpha, Ponzi scheme, quantitative trading / quantitative finance, railway mania, Ralph Waldo Emerson, Richard Feynman, Richard Feynman, risk/return, Saturday Night Live, self-driving car, sovereign wealth fund, the map is not the territory, The Predators' Ball, the scientific method, Thomas Kuhn: the structure of scientific revolutions, too big to fail, transaction costs, tulip mania, Turing machine, Turing test, yield curve

The bank/dealer borrows securities through securities lending transactions to cover its own and its clients’ short positions. 16. Though, as a practical matter, many apparently unleveraged asset managers have leverage gained through secured-lending transactions and derivative exposure. And even absent leverage, institutions can also be put into forced selling mode, either through redemptions or through violating risk and asset allocation constraints. 17. To keep from getting too far into the weeds, I haven’t included some of the details of the flows of funding and collateral through other intermediary agents, such as triparty agents like Bank of New York Mellon Corporation, JP Morgan, and Euroclear (though JP Morgan and BNY Mellon will appear when I discuss the 2008 crisis); repo central counterparties like Fixed Income Clearing Corporation, LCH.


pages: 602 words: 120,848

Winner-Take-All Politics: How Washington Made the Rich Richer-And Turned Its Back on the Middle Class by Paul Pierson, Jacob S. Hacker

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accounting loophole / creative accounting, active measures, affirmative action, asset allocation, barriers to entry, Bonfire of the Vanities, business climate, carried interest, Cass Sunstein, clean water, collective bargaining, corporate governance, Credit Default Swap, David Brooks, desegregation, employer provided health coverage, financial deregulation, financial innovation, financial intermediation, fixed income, full employment, Home mortgage interest deduction, Howard Zinn, income inequality, invisible hand, knowledge economy, laissez-faire capitalism, Martin Wolf, medical bankruptcy, moral hazard, Nate Silver, new economy, night-watchman state, offshore financial centre, oil shock, Powell Memorandum, Ralph Nader, Ronald Reagan, shareholder value, Silicon Valley, The Wealth of Nations by Adam Smith, too big to fail, trickle-down economics, union organizing, very high income, War on Poverty, winner-take-all economy, women in the workforce

Economic Mobility Initiative: An Initiative of the Pew Charitable Trusts (February 2008). 17 Wojciech Kopczuk, Emmanuel Saez, and Jae Song, “Uncovering the American Dream: Inequality and Mobility in Social Security Earnings Data Since 1937,” National Bureau of Economic Research (NBER) Working Paper No. 13345 (August 2007), 14, 40. 18 Miles Corak, “Chasing the Same Dream, Climbing Different Ladders: Economic Mobility in the United States and Canada,” Economic Mobility Initiative: An Initiative of the Pew Charitable Trusts (January 2009), 7. 19 See table 3.13: Change in Private Sector Employer-Provided Pension Coverage, 1979–2006 in Lawrence Mishel, Jared Bernstein, and Heidi Shierholz, The State of Working America 2008/2009 (Cornell: Cornell University Press, 2008). 20 Jack VanDerhei, Sarah Holden, and Luis Alonso, “401(k) Plan Asset Allocation, Account Balances, and Loan Activity in 2008,” Employee Benefit Research Institute No. 335 (October 2009): 16. 21 Alicia H. Munnell, Anthony Webb, and Francesca Golub-Sass, “The National Retirement Risk Index: After the Crash,” Center for Retirement Research at Boston College Brief No. 9–22 (October 2009). 22 David Himmelstein, Deborah Thorne, Elizabeth Warren, and Steffie Woolhandler, “Medical Bankruptcy in the United States, 2007: Results of a National Study,” American Journal of Medicine 122: 8 (2007): 741–746. 23 Organization for Economic Cooperation and Development, OECD Health Data 2009—Frequently Requested Data (November 2009), http://www.irdes.fr/EcoSante/DownLoad/OECDHealthData_FrequentlyRequestedData.xls. 24 Jacob S.


pages: 487 words: 151,810

The Social Animal: The Hidden Sources of Love, Character, and Achievement by David Brooks

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Albert Einstein, asset allocation, assortative mating, Atul Gawande, Bernie Madoff, business process, Cass Sunstein, choice architecture, clean water, creative destruction, Daniel Kahneman / Amos Tversky, David Brooks, delayed gratification, deliberate practice, disintermediation, Donald Trump, Douglas Hofstadter, Emanuel Derman, en.wikipedia.org, fear of failure, financial deregulation, financial independence, Flynn Effect, George Akerlof, Henri Poincaré, hiring and firing, impulse control, invisible hand, Joseph Schumpeter, labor-force participation, loss aversion, medical residency, meta analysis, meta-analysis, Monroe Doctrine, Paul Samuelson, Richard Thaler, risk tolerance, Robert Shiller, Robert Shiller, school vouchers, six sigma, Steve Jobs, Steven Pinker, the scientific method, The Spirit Level, The Wealth of Nations by Adam Smith, Thorstein Veblen, transaction costs, Walter Mischel, young professional

People who are given a prescription pain reliever they are told costs $2.50 a pill experience much more pain relief than those given what they are told is a 10-cent pill (even though all the pills are placebos). As Jonah Lehrer writes, “Their predictions became self-fulfilling prophecies.” Then there is inertia. The mind is a cognitive miser. It doesn’t like to expend mental energy. As a result people have a bias toward maintaining the status quo. TIAA-CREF offers college professors a range of asset-allocation options for their retirement accounts. According to one study, most of the participants in those plans make zero allocation changes during their entire professional careers. They just stick with whatever was the first option when they signed up. Then there is arousal. People think differently depending on their state of mind. A bank in South Africa worked with Harvard economist Sendhil Mullainathan to conduct an experiment to see what sort of loan-solicitation letters worked best.


pages: 467 words: 154,960

Trend Following: How Great Traders Make Millions in Up or Down Markets by Michael W. Covel

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Albert Einstein, asset allocation, Atul Gawande, backtesting, beat the dealer, Bernie Madoff, Black Swan, buy low sell high, capital asset pricing model, Clayton Christensen, commodity trading advisor, computerized trading, correlation coefficient, Daniel Kahneman / Amos Tversky, delayed gratification, deliberate practice, diversification, diversified portfolio, Edward Thorp, Elliott wave, Emanuel Derman, Eugene Fama: efficient market hypothesis, Everything should be made as simple as possible, fiat currency, fixed income, game design, hindsight bias, housing crisis, index fund, Isaac Newton, John Meriwether, John Nash: game theory, linear programming, Long Term Capital Management, mandelbrot fractal, margin call, market bubble, market fundamentalism, market microstructure, mental accounting, money market fund, Myron Scholes, Nash equilibrium, new economy, Nick Leeson, Ponzi scheme, prediction markets, random walk, Renaissance Technologies, Richard Feynman, Richard Feynman, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, shareholder value, Sharpe ratio, short selling, South Sea Bubble, Stephen Hawking, survivorship bias, systematic trading, the scientific method, Thomas L Friedman, too big to fail, transaction costs, upwardly mobile, value at risk, Vanguard fund, volatility arbitrage, William of Occam, zero-sum game

But now that the story has been got across better, people are, I think, realizing that Winton is a good horse to back in the race…” 105 If you were to put all the trend following models side by side, you would probably find that most made profits and incurred losses in the same markets. They were all looking at the same charts and obtaining the same perception of opportunity. Marc Goodman, Kenmar Asset Allocation16 106 Trend Following (Updated Edition): Learn to Make Millions in Up or Down Markets Drawdowns With volatility comes the inevitable drawdown. What do I mean? A drawdown is any losing period during an investment record. It is defined as the percent retrenchment from an equity peak to an equity valley. A drawdown is in effect from the time an equity retrenchment begins until a new equity high is reached, i.e., in terms of time, a drawdown encompasses both the period from equity peak to equity valley (length) and the time from the equity valley to a new equity high (recovery).15 For example, if you start from $100,000 and drop to $50,000, you are in a 50 percent drawdown.


pages: 476 words: 118,381

Space Chronicles: Facing the Ultimate Frontier by Neil Degrasse Tyson, Avis Lang

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Albert Einstein, Arthur Eddington, asset allocation, Berlin Wall, carbon-based life, centralized clearinghouse, cosmic abundance, cosmic microwave background, dark matter, Gordon Gekko, informal economy, invention of movable type, invention of the telescope, Isaac Newton, Karl Jansky, Kuiper Belt, Louis Blériot, Mars Rover, mutually assured destruction, Pluto: dwarf planet, RAND corporation, Ronald Reagan, Search for Extraterrestrial Intelligence, SETI@home, space pen, stem cell, Stephen Hawking, Steve Jobs, the scientific method, trade route, V2 rocket

If the President decides to proceed with a permanent replacement for any Russian element in the critical path or any Russian launch services, the President shall notify Congress of the reasons and the justification for the decision to proceed with the permanent replacement and the costs associated with the decision. (c) Assurances.—The United States shall seek assurances from the Russian Government that it places a higher priority on fulfilling its commitments to the International Space Station than it places on extending the life of the Mir Space Station, including assurances that Russia will not utilize assets allocated by Russia to the International Space Station for other purposes, including extending the life of Mir. (d) Equitable Utilization.—In the event that any International Partner in the International Space Station Program willfully violates any of its commitments or agreements for the provision of agreed upon Space Station-related hardware or related goods or services, the Administrator should, in a manner consistent with relevant international agreements, seek a commensurate reduction in the utilization rights of that Partner until such time as the violated commitments or agreements have been fulfilled.


pages: 471 words: 124,585

The Ascent of Money: A Financial History of the World by Niall Ferguson

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Admiral Zheng, Andrei Shleifer, Asian financial crisis, asset allocation, asset-backed security, Atahualpa, bank run, banking crisis, banks create money, Black Swan, Black-Scholes formula, Bonfire of the Vanities, Bretton Woods, BRICs, British Empire, capital asset pricing model, capital controls, Carmen Reinhart, Cass Sunstein, central bank independence, collateralized debt obligation, colonial exploitation, commoditize, Corn Laws, corporate governance, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, currency peg, Daniel Kahneman / Amos Tversky, deglobalization, diversification, diversified portfolio, double entry bookkeeping, Edmond Halley, Edward Glaeser, Edward Lloyd's coffeehouse, financial innovation, financial intermediation, fixed income, floating exchange rates, Fractional reserve banking, Francisco Pizarro, full employment, German hyperinflation, Hernando de Soto, high net worth, hindsight bias, Home mortgage interest deduction, Hyman Minsky, income inequality, information asymmetry, interest rate swap, Intergovernmental Panel on Climate Change (IPCC), Isaac Newton, iterative process, John Meriwether, joint-stock company, joint-stock limited liability company, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, knowledge economy, labour mobility, Landlord’s Game, liberal capitalism, London Interbank Offered Rate, Long Term Capital Management, market bubble, market fundamentalism, means of production, Mikhail Gorbachev, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, mortgage debt, mortgage tax deduction, Myron Scholes, Naomi Klein, negative equity, Nick Leeson, Northern Rock, Parag Khanna, pension reform, price anchoring, price stability, principal–agent problem, probability theory / Blaise Pascal / Pierre de Fermat, profit motive, quantitative hedge fund, RAND corporation, random walk, rent control, rent-seeking, reserve currency, Richard Thaler, Robert Shiller, Robert Shiller, Ronald Reagan, savings glut, seigniorage, short selling, Silicon Valley, South Sea Bubble, sovereign wealth fund, spice trade, structural adjustment programs, technology bubble, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Bayes, Thomas Malthus, Thorstein Veblen, too big to fail, transaction costs, value at risk, Washington Consensus, Yom Kippur War

It represents a one-way, totally unhedged bet on one market: the property market. Unfortunately, as we shall see in the next chapter, a bet on bricks and mortar is very far from being as safe as houses. And you do not need to live in New Orleans to find that out the hard way. 5 Safe as Houses It is the English-speaking world’s favourite economic game: property. No other facet of financial life has such a hold on the popular imagination. No other asset-allocation decision has inspired so many dinner-party conversations. The real estate market is unique. Every adult, no matter how economically illiterate, has a view on its future prospects. Even children are taught how to climb the property ladder, long before they have money of their own.al And the way we teach them is literally to play a property game. The game we know today as Monopoly was first devised in 1903 by an American woman, Elizabeth (‘Lizzie’) Phillips, a devotee of the radical economist Henry George.


pages: 320 words: 33,385

Market Risk Analysis, Quantitative Methods in Finance by Carol Alexander

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asset allocation, backtesting, barriers to entry, Brownian motion, capital asset pricing model, constrained optimization, credit crunch, Credit Default Swap, discounted cash flows, discrete time, diversification, diversified portfolio, en.wikipedia.org, fixed income, implied volatility, interest rate swap, market friction, market microstructure, p-value, performance metric, quantitative trading / quantitative finance, random walk, risk tolerance, risk-adjusted returns, risk/return, Sharpe ratio, statistical arbitrage, statistical model, stochastic process, stochastic volatility, Thomas Bayes, transaction costs, value at risk, volatility smile, Wiener process, yield curve, zero-sum game

Jarrow, R. and Rudd, A. (1982) Approximate option valuation for arbitrary stochastic processes. Journal of Financial Economics 10, 347–369. Jensen, M., (1969) Risk, the pricing of capital assets, and the evaluation of investment portfolios. Journal of Business, 42, 167–247. Joanes, D.N. and Gill, C.A. (1998) Comparing measures of sample skewness and kurtosis. The Statistician 47, 183–189. Jurczenko, E. and Maillet, B. (2006) Multi-moment Asset Allocation and Pricing Models. John Wiley & Sons, Ltd, Chichester. Kaplan, P. and Knowles, J. (2004) Kappa: A generalised downside-risk performance measure. Journal of Performance Measurement 8, 42–54. Keating, C. and Shadwick, F. (2002) A universal performance measure. Journal of Performance Measurement, 6, 59–84. Kim, S.J., Moshirian, F. and Wu, E. (2005) Dynamic stock market integration driven by the European Monetary Union: An empirical analysis.


pages: 545 words: 137,789

How Markets Fail: The Logic of Economic Calamities by John Cassidy

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Albert Einstein, Andrei Shleifer, anti-communist, asset allocation, asset-backed security, availability heuristic, bank run, banking crisis, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Black-Scholes formula, Bretton Woods, British Empire, capital asset pricing model, centralized clearinghouse, collateralized debt obligation, Columbine, conceptual framework, Corn Laws, corporate raider, correlation coefficient, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, Daniel Kahneman / Amos Tversky, debt deflation, diversification, Elliott wave, Eugene Fama: efficient market hypothesis, financial deregulation, financial innovation, Financial Instability Hypothesis, financial intermediation, full employment, George Akerlof, global supply chain, Gunnar Myrdal, Haight Ashbury, hiring and firing, Hyman Minsky, income per capita, incomplete markets, index fund, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), invisible hand, John Nash: game theory, John von Neumann, Joseph Schumpeter, Kenneth Arrow, laissez-faire capitalism, Landlord’s Game, liquidity trap, London Interbank Offered Rate, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, margin call, market bubble, market clearing, mental accounting, Mikhail Gorbachev, money market fund, Mont Pelerin Society, moral hazard, mortgage debt, Myron Scholes, Naomi Klein, negative equity, Network effects, Nick Leeson, Northern Rock, paradox of thrift, Pareto efficiency, Paul Samuelson, Ponzi scheme, price discrimination, price stability, principal–agent problem, profit maximization, quantitative trading / quantitative finance, race to the bottom, Ralph Nader, RAND corporation, random walk, Renaissance Technologies, rent control, Richard Thaler, risk tolerance, risk-adjusted returns, road to serfdom, Robert Shiller, Robert Shiller, Ronald Coase, Ronald Reagan, shareholder value, short selling, Silicon Valley, South Sea Bubble, sovereign wealth fund, statistical model, technology bubble, The Chicago School, The Great Moderation, The Market for Lemons, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, unorthodox policies, value at risk, Vanguard fund, Vilfredo Pareto, wealth creators, zero-sum game

At companies where employees have to opt into their retirement plans, only about half of those eligible bother to do so within the first year. At companies where employees are automatically enrolled, with an option to opt out, some nine in ten employees accept the automatic enrollment and make their monthly contributions. This acute form of “status quo” bias extends to the investment choices people make in their 401(k) plans. In plans that offer a default asset allocation—a mixture of stocks and bonds, usually—about three quarters of all participants accept it. Similarly, if a plan’s default option involves investing in the parent company’s stock, many people accept that, too. “[T]his pattern of investment was unaffected by the prominent bankruptcies of Enron, WorldCom, Global Crossing, and many other firms in the aftermath of the collapse of the technology bubble,” Laibson notes.


pages: 524 words: 143,993

The Shifts and the Shocks: What We've Learned--And Have Still to Learn--From the Financial Crisis by Martin Wolf

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air freight, anti-communist, Asian financial crisis, asset allocation, asset-backed security, balance sheet recession, bank run, banking crisis, banks create money, Basel III, Ben Bernanke: helicopter money, Berlin Wall, Black Swan, bonus culture, break the buck, Bretton Woods, call centre, capital asset pricing model, capital controls, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, central bank independence, collateralized debt obligation, corporate governance, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, currency peg, debt deflation, deglobalization, Deng Xiaoping, diversification, double entry bookkeeping, en.wikipedia.org, Erik Brynjolfsson, Eugene Fama: efficient market hypothesis, eurozone crisis, Fall of the Berlin Wall, fiat currency, financial deregulation, financial innovation, financial repression, floating exchange rates, forward guidance, Fractional reserve banking, full employment, global rebalancing, global reserve currency, Growth in a Time of Debt, Hyman Minsky, income inequality, inflation targeting, information asymmetry, invisible hand, Joseph Schumpeter, Kenneth Rogoff, labour market flexibility, labour mobility, light touch regulation, liquidationism / Banker’s doctrine / the Treasury view, liquidity trap, Long Term Capital Management, mandatory minimum, margin call, market bubble, market clearing, market fragmentation, Martin Wolf, Mexican peso crisis / tequila crisis, money market fund, moral hazard, mortgage debt, negative equity, new economy, North Sea oil, Northern Rock, open economy, paradox of thrift, Paul Samuelson, price stability, private sector deleveraging, purchasing power parity, pushing on a string, quantitative easing, Real Time Gross Settlement, regulatory arbitrage, reserve currency, Richard Feynman, Richard Feynman, risk-adjusted returns, risk/return, road to serfdom, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Reagan, savings glut, Second Machine Age, secular stagnation, shareholder value, short selling, sovereign wealth fund, special drawing rights, The Chicago School, The Great Moderation, The Market for Lemons, the market place, The Myth of the Rational Market, the payments system, The Wealth of Nations by Adam Smith, too big to fail, Tyler Cowen: Great Stagnation, very high income, winner-take-all economy, zero-sum game

Basel III A first area of focus was reaching agreement on a new Basel III accord (after the failures of Basel I and II demonstrated by the crisis) governing bank capital, risk-management – including management of market risk – macroprudential regulation and liquidity risk.4 Basel I, which imposed a minimum set of capital requirements for banks, had been agreed by the Basel Committee on Banking Supervision in 1988. Ironically, one of its main aims was to weaken the feared competition from undercapitalized Japanese banks, which then promptly failed in the financial crisis of the 1990s. The essence of Basel I was risk-weighting of assets, with assets allocated to five risk classes. Ironically and dangerously, these weights treated government debt as riskless and put triple-A-rated mortgage-backed securities into the next least risky category. International banks were required to fund themselves with capital equal to 8 per cent of their risk-weighted assets. But that meant far lower ratios of equity capital to assets if the risk weights of many of the assets that individual institutions held were themselves low.5 Basel II, initially published in 2004, was an extension of Basel I.


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Why Stock Markets Crash: Critical Events in Complex Financial Systems by Didier Sornette

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Asian financial crisis, asset allocation, Berlin Wall, Bretton Woods, Brownian motion, capital asset pricing model, capital controls, continuous double auction, currency peg, Deng Xiaoping, discrete time, diversified portfolio, Elliott wave, Erdős number, experimental economics, financial innovation, floating exchange rates, frictionless, frictionless market, full employment, global village, implied volatility, index fund, information asymmetry, intangible asset, invisible hand, John von Neumann, joint-stock company, law of one price, Louis Bachelier, mandelbrot fractal, margin call, market bubble, market clearing, market design, market fundamentalism, mental accounting, moral hazard, Network effects, new economy, oil shock, open economy, pattern recognition, Paul Erdős, Paul Samuelson, quantitative trading / quantitative finance, random walk, risk/return, Ronald Reagan, Schrödinger's Cat, selection bias, short selling, Silicon Valley, South Sea Bubble, statistical model, stochastic process, Tacoma Narrows Bridge, technological singularity, The Coming Technological Singularity, The Wealth of Nations by Adam Smith, Tobin tax, total factor productivity, transaction costs, tulip mania, VA Linux, Y2K, yield curve

An Introduction to Econophysics: Correlations and Complexity in Finance (Cambridge University Press, Cambridge, U.K. and New York). 288. Markowitz, H. (1959). Portfolio Selection: Efficient Diversification of Investment (Wiley, New York). 289. Mauboussin, M. J. and Hiler, R. (1999). Rational Exuberance? Equity research report of Credit Suisse First Boston, January 26. 290. Maug, E. and Naik, N. (1995). Herding and Delegated Portfolio Management: The Impact of Relative Performance Evaluation on Asset Allocation, Working paper, Duke University, Durham, NC. 291. McCarty, P. A. (1986). Effects of feedback on the self-confidence of men and women, Academy of Management Journal 29, 840–847. 292. Meakin, P. (1998). Fractals, Scaling, and Growth Far from Equilibrium (Cambridge University Press, Cambridge, U.K. and New York). 293. Merton, R. (1973). An intertemporal capital asset pricing model, Econometrica 41, 867–888. 294.


pages: 444 words: 151,136

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

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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, 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, 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, The Great Moderation, the scientific method, time value of money, too big to fail, upwardly mobile, War on Poverty, Yogi Berra, young professional

Titled On a Clear Day Unknown Unknowns 13 You Can See 2,000, the research report seemed unbelievable, since the market had been stalled beneath 1,000 for about a decade.6 On the other side of the coin is a graveyard filled with the intellects that have sought to challenge the wisdom of compounding credit growth at a rate significantly greater than real economic growth. There is a good reason for this: as Ibbotson and Sinquefield have shown, longterm returns of the stock market have been high, reflecting risk and a premium over inflation. From 1925 to 2007, large-cap stocks averaged a total return of 10.4 percent, while inflation was just 3 percent (using the official yardstick).7 There are no straightforward decision rules for asset allocation that can be gleaned from fundamental data that are stable and reliable over time; so the conventional wisdom is that it is best to stick with stocks unless you have some need for money in the next few years. In the late 1980s, Charlie Minter and his partner Stan Selvigson warned of a coming credit crisis. Although they were utterly wrong, their convincing graphics and articulate commentary was welcomed (but rarely acted upon) by institutional investors weary of continuously upbeat forecasts from other strategists.


pages: 466 words: 127,728

The Death of Money: The Coming Collapse of the International Monetary System by James Rickards

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Affordable Care Act / Obamacare, Asian financial crisis, asset allocation, Ayatollah Khomeini, bank run, banking crisis, Ben Bernanke: helicopter money, bitcoin, Black Swan, Bretton Woods, BRICs, business climate, capital controls, Carmen Reinhart, central bank independence, centre right, collateralized debt obligation, collective bargaining, complexity theory, computer age, credit crunch, currency peg, David Graeber, debt deflation, Deng Xiaoping, diversification, Edward Snowden, eurozone crisis, fiat currency, financial innovation, financial intermediation, financial repression, fixed income, Flash crash, floating exchange rates, forward guidance, G4S, George Akerlof, global reserve currency, global supply chain, Growth in a Time of Debt, income inequality, inflation targeting, information asymmetry, invisible hand, jitney, John Meriwether, Kenneth Rogoff, labor-force participation, labour mobility, Lao Tzu, liquidationism / Banker’s doctrine / the Treasury view, liquidity trap, Long Term Capital Management, mandelbrot fractal, margin call, market bubble, market clearing, market design, money market fund, money: store of value / unit of account / medium of exchange, mutually assured destruction, obamacare, offshore financial centre, oil shale / tar sands, open economy, Plutocrats, plutocrats, Ponzi scheme, price stability, quantitative easing, RAND corporation, reserve currency, risk-adjusted returns, Rod Stewart played at Stephen Schwarzman birthday party, Ronald Reagan, Satoshi Nakamoto, Silicon Valley, Silicon Valley startup, Skype, sovereign wealth fund, special drawing rights, Stuxnet, The Market for Lemons, Thomas Kuhn: the structure of scientific revolutions, Thomas L Friedman, too big to fail, trade route, uranium enrichment, Washington Consensus, working-age population, yield curve

Whether the loss of confidence in the dollar results from external threats or internal neglect, investors should ask two questions: What comes next? and How can wealth be preserved in the transition? ■ Three Paths The dollar’s demise will take one of three paths. The first is world money, the SDR; the second is a gold standard; and the third is social disorder. Each of these outcomes can be foreseen, and each presents an asset-allocation strategy best able to preserve wealth. The substitution of SDRs for dollars as the global reserve currency is already under way, and the IMF has laid out a ten-year transition plan that the United States has informally endorsed. This blueprint involves increasing the amount of SDRs in circulation and building out an infrastructure of SDR-denominated investable assets, issuers, investors, and dealers.


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Connectography: Mapping the Future of Global Civilization by Parag Khanna

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1919 Motor Transport Corps convoy, 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, 9 dash line, additive manufacturing, Admiral Zheng, affirmative action, agricultural Revolution, Airbnb, Albert Einstein, amateurs talk tactics, professionals talk logistics, Amazon Mechanical Turk, Asian financial crisis, asset allocation, autonomous vehicles, banking crisis, Basel III, Berlin Wall, bitcoin, Black Swan, blockchain, borderless world, Boycotts of Israel, Branko Milanovic, BRICs, British Empire, business intelligence, call centre, capital controls, charter city, clean water, cloud computing, collateralized debt obligation, commoditize, complexity theory, continuation of politics by other means, corporate governance, corporate social responsibility, credit crunch, crony capitalism, crowdsourcing, cryptocurrency, cuban missile crisis, data is the new oil, David Ricardo: comparative advantage, deglobalization, deindustrialization, dematerialisation, Deng Xiaoping, Detroit bankruptcy, digital map, diversification, Doha Development Round, edge city, Edward Snowden, Elon Musk, energy security, ethereum blockchain, European colonialism, eurozone crisis, failed state, Fall of the Berlin Wall, family office, Ferguson, Missouri, financial innovation, financial repression, fixed income, forward guidance, global supply chain, global value chain, global village, Google Earth, Hernando de Soto, high net worth, Hyperloop, ice-free Arctic, if you build it, they will come, illegal immigration, income inequality, income per capita, industrial cluster, industrial robot, informal economy, Infrastructure as a Service, interest rate swap, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Isaac Newton, Jane Jacobs, Jaron Lanier, John von Neumann, Julian Assange, Just-in-time delivery, Kevin Kelly, Khyber Pass, Kibera, Kickstarter, labour market flexibility, labour mobility, LNG terminal, low cost carrier, manufacturing employment, mass affluent, mass immigration, megacity, Mercator projection, Metcalfe’s law, microcredit, mittelstand, Monroe Doctrine, mutually assured destruction, New Economic Geography, new economy, New Urbanism, off grid, offshore financial centre, oil rush, oil shale / tar sands, oil shock, openstreetmap, out of africa, Panamax, Parag Khanna, Peace of Westphalia, peak oil, Pearl River Delta, Peter Thiel, Philip Mirowski, Plutocrats, plutocrats, post-oil, post-Panamax, private military company, purchasing power parity, QWERTY keyboard, race to the bottom, Rana Plaza, rent-seeking, reserve currency, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Coase, Scramble for Africa, Second Machine Age, sharing economy, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, six sigma, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, South China Sea, South Sea Bubble, sovereign wealth fund, special economic zone, spice trade, Stuxnet, supply-chain management, sustainable-tourism, TaskRabbit, telepresence, the built environment, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, Tim Cook: Apple, trade route, transaction costs, UNCLOS, uranium enrichment, urban planning, urban sprawl, WikiLeaks, young professional, zero day

The Australian counterinsurgency expert David Kilcullen points out that as the world becomes crowded and coastal, militaries need high-resolution three-dimensional terrain maps of informal settlements. 8. The subsequent volumes of Hardt and Negri’s trilogy, Multitude and Commonwealth, continue this intellectual struggle against capitalism’s appropriation of property, advocating instead greater unity among dispersed communities of peoples. 9. One estimate suggests $2 trillion in emerging market pension assets allocated to other emerging markets by 2020. See Jay Pelosky, “Emerging Market Portfolio Globalization: The Next Big Thing” (New America Foundation, World Economic Roundtable policy paper, July 17, 2014). 10. Martin Neil Baily and Douglas J. Elliott, “The Role of Finance in the Economy: Implications for Structural Reform of the Financial Sector” (Brookings Institution, July 11, 2013). CHAPTER 14: CYBER CIVILIZATION AND ITS DISCONTENTS 1.


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A Splendid Exchange: How Trade Shaped the World by William J. Bernstein

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Admiral Zheng, asset allocation, bank run, Benoit Mandelbrot, British Empire, call centre, clean water, Columbian Exchange, Corn Laws, David Ricardo: comparative advantage, deindustrialization, Doha Development Round, domestication of the camel, double entry bookkeeping, Eratosthenes, financial innovation, Gini coefficient, God and Mammon, ice-free Arctic, imperial preference, income inequality, intermodal, James Hargreaves, John Harrison: Longitude, Khyber Pass, low skilled workers, non-tariff barriers, Paul Samuelson, placebo effect, Port of Oakland, refrigerator car, Silicon Valley, South China Sea, South Sea Bubble, spice trade, spinning jenny, Steven Pinker, The Wealth of Nations by Adam Smith, Thomas L Friedman, Thomas Malthus, trade liberalization, trade route, transatlantic slave trade, transatlantic slave trade, transcontinental railway, upwardly mobile, working poor, zero-sum game

Also by William J. Bernstein The Intelligent Asset Allocator The Four Pillars of Investing The Birth of Plenty WILLIAM J. BERNSTEIN To Jane List of Maps ix Introduction 1 1 Sumer 20 2 The Straits of Trade 43 3 Camels, Perfumes, and Prophets 54 4 The Baghdad-Canton Express 77 5 The Taste of Trade and the Captives of Trade 110 6 The Disease of Trade 130 7 Da Gama's Urge 152 8 A World Encompassed 198 9 The Coming of Corporations 214 10 Transplants 241 11 The Triumph and Tragedy of Free Trade 280 12 What Henry Bessemer Wrought 316 13 Collapse 338 14 The Battle of Seattle 366 Acknowledgments 387 Notes 389 Bibliography 429 Illustration Credits 449 Ancient Silk Routes 3 World Trade System, Third Millennium BC 25 Ancient Canals at Suez 37 Winter Monsoon Winds and Summer Monsoon Winds 39 Athenian Grain Routes 45 Incense Lands and Routes 63 The World of Medieval Trade 80 The Spice Islands 114 Eastern Mediterranean Spice/Slave Trade, Circa AD 1250 126 The Black Death, Act I: AD 540-800 137 The Black Death, Act II: 1330-1350 141 The Tordesillas Line in the West 169 Da Gama's First Voyage, 1497-1499 171 The Global Wind Machine 201 Banda (Nutmeg) Islands 227 Strait of Hormuz 231 Dutch Empire in Asia at its Height in the Seventeenth Century 233 Coffee-Growing Area and Ports of Late-Medieval Yemen 250 The Sugar Islands 269 Pearl River Estuary 285 The Erie Canal and Saint Lawrence Systems in 1846 325 World Oil Flows, Millions of Barrels per Day 368 The circumstances could not have been more ordinary: a September morning in a hotel lobby in central Berlin.


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Makers and Takers: The Rise of Finance and the Fall of American Business by Rana Foroohar

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3D printing, accounting loophole / creative accounting, activist fund / activist shareholder / activist investor, additive manufacturing, Airbnb, algorithmic trading, Alvin Roth, Asian financial crisis, asset allocation, bank run, Basel III, bonus culture, Bretton Woods, British Empire, call centre, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, carried interest, centralized clearinghouse, clean water, collateralized debt obligation, commoditize, computerized trading, corporate governance, corporate raider, corporate social responsibility, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, crowdsourcing, David Graeber, deskilling, Detroit bankruptcy, diversification, Double Irish / Dutch Sandwich, Emanuel Derman, Eugene Fama: efficient market hypothesis, financial deregulation, financial intermediation, Frederick Winslow Taylor, George Akerlof, gig economy, Goldman Sachs: Vampire Squid, Gordon Gekko, greed is good, High speed trading, Home mortgage interest deduction, housing crisis, Howard Rheingold, Hyman Minsky, income inequality, index fund, information asymmetry, interest rate derivative, interest rate swap, Internet of things, invisible hand, John Markoff, joint-stock company, joint-stock limited liability company, Kenneth Rogoff, knowledge economy, labor-force participation, labour mobility, London Whale, Long Term Capital Management, manufacturing employment, market design, Martin Wolf, money market fund, moral hazard, mortgage debt, mortgage tax deduction, new economy, non-tariff barriers, offshore financial centre, oil shock, passive investing, Paul Samuelson, pensions crisis, Ponzi scheme, principal–agent problem, quantitative easing, quantitative trading / quantitative finance, race to the bottom, Ralph Nader, Rana Plaza, RAND corporation, random walk, rent control, Robert Shiller, Robert Shiller, Ronald Reagan, Satyajit Das, Second Machine Age, shareholder value, sharing economy, Silicon Valley, Silicon Valley startup, Snapchat, sovereign wealth fund, Steve Jobs, technology bubble, The Chicago School, the new new thing, The Spirit Level, The Wealth of Nations by Adam Smith, Tim Cook: Apple, Tobin tax, too big to fail, trickle-down economics, Tyler Cowen: Great Stagnation, Vanguard fund, zero-sum game

“Congress did not intend for [401(k)s] to replace traditional pensions as a primary retirement vehicle, and they are poorly designed for this role,” says Monique Morrissey, an economist at the Economic Policy Institute who testified to the Senate on the topic in 2014. “Few people have the math skills, financial sophistication, or time to make sense of often conflicting financial advice and make sound investment decisions.” The complexity of the system results in high numbers of people taking money out early, squandering the tax benefits of such programs, or simply making bad choices in terms of asset allocation. Indeed, anyone who has ever tried to pore over the benefits websites of their employer to try to make the smartest decision (or, God forbid, call the help line “advisers”) knows what she means. Even for people who know something about finance it’s a confusing maze of options, and as behavioral economics research shows us, more options often result in bad decisions or no decision at all.29 IRAs, which freelancers and people who don’t have access to 401(k)s use to save, are even worse, since they offer fewer investor protections and typically have even higher fees.30 Yet bad policy decisions and the desire of both the public and private sector to push retirement responsibilities onto individuals have resulted in a system where such programs are now the norm for most people—or at least most wealthy people.


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Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian, Tom Griffiths

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4chan, Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, algorithmic trading, anthropic principle, asset allocation, autonomous vehicles, Bayesian statistics, Berlin Wall, Bill Duvall, bitcoin, Community Supported Agriculture, complexity theory, constrained optimization, cosmological principle, cryptocurrency, Danny Hillis, David Heinemeier Hansson, delayed gratification, dematerialisation, diversification, Donald Knuth, double helix, Elon Musk, fault tolerance, Fellow of the Royal Society, Firefox, first-price auction, Flash crash, Frederick Winslow Taylor, George Akerlof, global supply chain, Google Chrome, Henri Poincaré, information retrieval, Internet Archive, Jeff Bezos, John Nash: game theory, John von Neumann, knapsack problem, Lao Tzu, Leonard Kleinrock, linear programming, martingale, Nash equilibrium, natural language processing, NP-complete, P = NP, packet switching, Pierre-Simon Laplace, prediction markets, race to the bottom, RAND corporation, RFC: Request For Comment, Robert X Cringely, sealed-bid auction, second-price auction, self-driving car, Silicon Valley, Skype, sorting algorithm, spectrum auction, Steve Jobs, stochastic process, Thomas Bayes, Thomas Malthus, traveling salesman, Turing machine, urban planning, Vickrey auction, Vilfredo Pareto, Walter Mischel, Y Combinator, zero-sum game

When it comes to portfolio management, it turns out that unless you’re highly confident in the information you have about the markets, you may actually be better off ignoring that information altogether. Applying Markowitz’s optimal portfolio allocation scheme requires having good estimates of the statistical properties of different investments. An error in those estimates can result in very different asset allocations, potentially increasing risk. In contrast, splitting your money evenly across stocks and bonds is not affected at all by what data you’ve observed. This strategy doesn’t even try to fit itself to the historical performance of those investment types—so there’s no way it can overfit. Of course, just using a fifty-fifty split is not necessarily the complexity sweet spot, but there’s something to be said for it.


The Blockchain Alternative: Rethinking Macroeconomic Policy and Economic Theory by Kariappa Bheemaiah

accounting loophole / creative accounting, Ada Lovelace, Airbnb, algorithmic trading, asset allocation, autonomous vehicles, balance sheet recession, bank run, banks create money, Basel III, basic income, Ben Bernanke: helicopter money, bitcoin, blockchain, Bretton Woods, business process, call centre, capital controls, Capital in the Twenty-First Century by Thomas Piketty, cashless society, cellular automata, central bank independence, Claude Shannon: information theory, cloud computing, cognitive dissonance, collateralized debt obligation, commoditize, complexity theory, constrained optimization, corporate governance, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crowdsourcing, cryptocurrency, David Graeber, deskilling, Diane Coyle, discrete time, distributed ledger, diversification, double entry bookkeeping, ethereum blockchain, fiat currency, financial innovation, financial intermediation, Flash crash, floating exchange rates, Fractional reserve banking, full employment, George Akerlof, illegal immigration, income inequality, income per capita, inflation targeting, information asymmetry, interest rate derivative, inventory management, invisible hand, John Maynard Keynes: technological unemployment, John von Neumann, joint-stock company, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, Kevin Kelly, knowledge economy, labour market flexibility, large denomination, liquidity trap, London Whale, low skilled workers, M-Pesa, Marc Andreessen, market bubble, market fundamentalism, Mexican peso crisis / tequila crisis, money market fund, money: store of value / unit of account / medium of exchange, mortgage debt, natural language processing, Network effects, new economy, Nikolai Kondratiev, offshore financial centre, packet switching, Pareto efficiency, pattern recognition, peer-to-peer lending, Ponzi scheme, precariat, pre–internet, price mechanism, price stability, private sector deleveraging, profit maximization, QR code, quantitative easing, quantitative trading / quantitative finance, Ray Kurzweil, Real Time Gross Settlement, rent control, rent-seeking, Satoshi Nakamoto, Satyajit Das, savings glut, seigniorage, Silicon Valley, Skype, smart contracts, software as a service, software is eating the world, speech recognition, statistical model, Stephen Hawking, supply-chain management, technology bubble, The Chicago School, The Future of Employment, The Great Moderation, the market place, The Nature of the Firm, the payments system, the scientific method, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, too big to fail, trade liberalization, transaction costs, Turing machine, Turing test, universal basic income, Von Neumann architecture, Washington Consensus

Portfolio insurers on the other hand, follow a strategy intended to guarantee a minimal level of wealth at a specified insurance expiration date. The insurers follow this strategy to ensure that their final losses will not exceed a certain fraction of their investment over this time period. Constant Proportion Portfolio Insurance (CPPI)- CPPI is a method of portfolio insurance in which the investor sets a floor on the value of his portfolio and then structures asset allocation around that decision. The two asset classes are classified as a risky asset (usually equities or mutual funds), and a riskless asset of either cash or Treasury bonds. The percentage allocated to each depends on how aggressive the investment strategy is. 31 204 Chapter 4 ■ Complexity Economics: A New Way to Witness Capitalism Every Rebalancer agents started in the simulation with the same value of their portfolio ($100,000), with half of it in stocks and half in cash.

Analysis of Financial Time Series by Ruey S. Tsay

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Asian financial crisis, asset allocation, Bayesian statistics, Black-Scholes formula, Brownian motion, capital asset pricing model, compound rate of return, correlation coefficient, data acquisition, discrete time, frictionless, frictionless market, implied volatility, index arbitrage, Long Term Capital Management, market microstructure, martingale, p-value, pattern recognition, random walk, risk tolerance, short selling, statistical model, stochastic process, stochastic volatility, telemarketer, transaction costs, value at risk, volatility smile, Wiener process, yield curve

ISBN: 0-471-41544-8 CHAPTER 9 Multivariate Volatility Models and Their Applications In this chapter, we generalize the univariate volatility models of Chapter 3 to the multivariate case and discuss some methods for simplifying the dynamic relationships between volatility processes of multiple asset returns. Multivariate volatilities have many important financial applications. They play an important role in portfolio selection and asset allocation, and they can be used to compute the Value at Risk of a financial position consisting of multiple assets. Consider a multivariate return series {rt }. We adopt the same approach as the univariate case by rewriting the series as rt = µt + at , where µt = E(rt | Ft−1 ) is the conditional expectation of rt given the past information Ft−1 , and at = (a1t , . . . , akt ) is the shock, or innovation, of the series at time t.


pages: 598 words: 172,137

Who Stole the American Dream? by Hedrick Smith

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Affordable Care Act / Obamacare, Airbus A320, airline deregulation, anti-communist, asset allocation, banking crisis, Bonfire of the Vanities, British Empire, business process, clean water, cloud computing, collateralized debt obligation, collective bargaining, commoditize, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, David Brooks, Deng Xiaoping, desegregation, Double Irish / Dutch Sandwich, family office, full employment, global supply chain, Gordon Gekko, guest worker program, hiring and firing, housing crisis, Howard Zinn, income inequality, index fund, industrial cluster, informal economy, invisible hand, Joseph Schumpeter, Kenneth Rogoff, Kitchen Debate, knowledge economy, knowledge worker, laissez-faire capitalism, late fees, Long Term Capital Management, low cost carrier, manufacturing employment, market fundamentalism, Maui Hawaii, mega-rich, mortgage debt, negative equity, new economy, Occupy movement, Own Your Own Home, Paul Samuelson, Peter Thiel, Plutonomy: Buying Luxury, Explaining Global Imbalances, Ponzi scheme, Powell Memorandum, Ralph Nader, RAND corporation, Renaissance Technologies, reshoring, rising living standards, Robert Bork, Robert Shiller, Robert Shiller, rolodex, Ronald Reagan, shareholder value, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, Steve Jobs, The Chicago School, The Spirit Level, too big to fail, transaction costs, transcontinental railway, union organizing, Unsafe at Any Speed, Vanguard fund, We are the 99%, women in the workforce, working poor, Y2K

Summers, Larry. “Executive Summary of Economic Policy Work.” Memo to President-Elect Barack Obama, December 15, 2008. http://​s3.​documentcloud.​org/​documents/​285065/​summers-​12-​15-​08-​memo.​pdf. VanDerhei, Jack. “Evaluation of the Adequacy and Structure of U.S. Voluntary Retirement Plans, with Special Emphasis on 401(k) Plans.” Benefits Quarterly, Third Quarter 2010. ———. “401(k) Plan Asset Allocation, Account Balances, and Loan Activity in2009.” EBRI Issue Brief No. 350, Employee Benefits Research Institute, Washington, DC, November 2010. ———. “Measuring Retirement Income Adequacy: Calculating Realistic Income Replacement Rates.” EBRI Issue Brief No. 297, Employee Benefits Research Institute, Washington, DC, September 2006. ———. “A Post-Crisis Assessment of Retirement Income Adequacy for Baby Boomers and Gen Xers.”


pages: 741 words: 179,454

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

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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, 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, 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, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, Kevin Kelly, labour market flexibility, 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, 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 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

—Yves Smith, Founder of www.nakedcapitalism.com and Author of ECONned: How Unenlightened Self Interest Undermined Democracy and Corrupted Capitalism “Most books written about the global financial crisis have been written by those who only became wise after the event. Das is not one of them. Long before the collapse of Lehman Brothers, he warned about the flaws in modern finance. Extreme Money is his account of what went wrong. Read it!” —Edward Chancellor, Member of GMO’s Asset Allocation Team and Author of Devil Take the Hindmost: A History of Financial Speculation “A rich analysis told with color and verve.” —Philip Augar, Author of Reckless: The Rise and Fall of the City Praise for Traders, Guns & Money “...a distinctly timely book...tries to reach out to the mathematically challenged to explain how the world of derivatives “really” works...explaining not only the high-minded theory behind the business and its various products but the sometimes sordid reality of the industry, illustrated by lively anecdotes...very up to date, covering some of the new areas of finance, such as credit derivatives...also gives an excellent sense of the all-important cultural aspect of the business, detailing the complexities of trading-floor politics, the dangerously skewed incentive systems, the obsession with money and the cultural chasm that separates derivative traders from many of their clients—and from many other parts of the bank.”


pages: 2,045 words: 566,714

J.K. Lasser's Your Income Tax by J K Lasser Institute

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Affordable Care Act / Obamacare, airline deregulation, asset allocation, collective bargaining, distributed generation, employer provided health coverage, estate planning, Home mortgage interest deduction, intangible asset, medical malpractice, medical residency, money market fund, mortgage debt, mortgage tax deduction, passive income, Ponzi scheme, profit motive, rent control, Right to Buy, telemarketer, transaction costs, urban renewal, zero-coupon bond

Where death occurred before 1982 and a surviving spouse materially participated in the operation of a farm or other business, the estate could have elected to treat the farm or business property as an “eligible joint interest,” which means that part of the investment in the property was attributed to the surviving spouse’s services and that part was not included in the deceased spouse’s estate. Where such an election was made, the survivor’s basis for income tax purposes includes the estate tax value of property included in the decedent’s estate. 5.19 Allocating Cost Among Several Assets Allocation of basis is generally required in these cases: when the property includes land and building; the land is to be divided into lots; securities or mutual-fund shares are purchased at different times; stock splits; and in the purchase of a business. Purchase of land and building. To figure depreciation on the building, part of the purchase price must be allocated to the building. The allocation is made according to the fair market values of the building and land.