15 results back to index
Expected Returns: An Investor's Guide to Harvesting Market Rewards by Antti Ilmanen
Andrei Shleifer, asset allocation, asset-backed security, availability heuristic, backtesting, balance sheet recession, bank run, banking crisis, barriers to entry, Bernie Madoff, Black Swan, Bretton Woods, buy low sell high, capital asset pricing model, capital controls, Carmen Reinhart, central bank independence, collateralized debt obligation, 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, 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, New Journalism, oil shock, p-value, passive investing, 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, Sharpe ratio, short selling, sovereign wealth fund, statistical arbitrage, statistical model, stochastic volatility, 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
The full integration of all countries into global markets is a hoped-for outcome, not a reality. Market frictions and illiquidity premia The impact of supply–demand factors—and of investor irrationalities—on asset prices is made possible by market frictions. Frictions related to illiquidity, funding constraints, and trading costs, as well as counterparty risk, agency concerns, and other information problems can be first-order important, as the 2008 experience shows. Bearish expectations, elevated risk, and risk aversion do not alone explain the distressed price levels of securitized bonds and other assets. Many financial intermediaries and investors became forced sellers as market frictions prevented them and other investors from taking advantage of good deals or nearly riskless arbitrage opportunities.
Opportunities that appeared compelling over the long horizon could not be taken due to the possibility that further de-levering and related mark-to-market volatility would make the investment positions unsustainable over the short run. A diverse literature on market frictions explains why asset prices might deviate from fair values or respond sluggishly to new information. However, few asset-pricing models relate asset risk premia to market frictions such as funding and liquidity constraints. Garleanu–Pedersen (2009a) propose a model in which the CAPM risk premium is boosted when binding funding constraints make capital scarce, while Acharya–Pedersen (2005) have adjusted the CAPM to include liquidity-related premia. Illiquidity is the most important market friction. Early studies of liquidity premia focused on the cost (rather than the risk) of illiquidity—they observed that greater trading costs when buying and selling assets would reduce expected net returns.
Peso problems and learning stories help in interpreting past return predictability but contain no lessons about future profit opportunities. Market frictions Most academic predictability evidence is presented without taking into account trading costs and other market frictions. It is not surprising, then, that paper profits tend to be most consistent in illiquid assets (e.g., small-cap stocks) or in trading styles that involve high turnover (e.g., short-term reversal). Faced with evidence of profitable trading strategies, it is always reasonable to question whether trading cost estimates (including both direct costs and market impact) have been understated. Fortunately, newer studies increasingly adjust profits for trading costs, financing costs, short-selling constraints, and other market frictions. While the limits-to-arbitrage literature explains why speculative capital is generally scarce, these adjustments explain why certain paper regularities are harder to exploit in practice than others.
Airbnb, airport security, Al Roth, Andrei Shleifer, attribution theory, autonomous vehicles, barriers to entry, Brownian motion, centralized clearinghouse, clean water, conceptual framework, constrained optimization, continuous double auction, deferred acceptance, Donald Trump, Edward Glaeser, experimental subject, first-price auction, framing effect, frictionless, fundamental attribution error, George Akerlof, Goldman Sachs: Vampire Squid, helicopter parent, Internet of things, invisible hand, Isaac Newton, iterative process, Jean Tirole, Jeff Bezos, Johann Wolfgang von Goethe, John Nash: game theory, John von Neumann, Joseph Schumpeter, late fees, linear programming, Lyft, market clearing, market design, market friction, medical residency, multi-sided market, mutually assured destruction, Nash equilibrium, Occupy movement, Peter Thiel, pets.com, pez dispenser, pre–internet, price mechanism, price stability, prisoner's dilemma, profit motive, proxy bid, RAND corporation, ride hailing / ride sharing, Robert Shiller, Robert Shiller, Ronald Coase, school choice, school vouchers, sealed-bid auction, second-price auction, second-price sealed-bid, sharing economy, Silicon Valley, spectrum auction, Steve Jobs, Tacoma Narrows Bridge, technoutopianism, telemarketer, The Market for Lemons, The Wisdom of Crowds, Thomas Malthus, Thorstein Veblen, trade route, transaction costs, two-sided market, uranium enrichment, Vickrey auction, winner-take-all economy
Airbnb is an epic leap forward when compared to the epic leap of faith involved in renting a room via its predecessors, the classified ads or Craigslist. But let’s not confuse a set of groundbreaking market innovations with the end of market frictions. Yes, there are entire websites devoted to Airbnb horror stories—the trashed homes, the tenant-turned-squatter. There’s an equal number of angry rants directed at Uber. Neither of us rents our idle real estate assets when we’re out of town and not because we’re old-fashioned. We’ve also experienced market frictions of a more mundane variety. In writing this book we went to Washington to interview George Akerlof of market-for-lemons fame. As a bit of add-on market research, one of us, Ray, decided to rent an apartment for the night via Airbnb. The renter’s credentials were impeccable.
But to get your $60 billion valuation, you need to create as many frictions as possible for everyone else. Although proponents of the sharing economy tout its ability to reduce market frictions, the only way they’re going to make the kinds of profits they (and their investors) want is to create new ones. That’s something they’re not interested in talking about to the public at large, or to their representatives in government. This leaves a bit of a paradox in the techno-utopian free-market narrative. A great entrepreneur will use technology to create a fantastic new market, then will use technology to set up market frictions to protect it. As entrepreneur and venture capitalist Peter Thiel wrote in the Wall Street Journal, “Competition Is for Losers.”12 Don’t get us wrong. We’re not faulting the market makers of Silicon Valley nor begrudging them for the profits they’ve generated and captured.
We need to figure out how to adapt our models to reality, not the other way around. Sharing Economists aren’t the only ones trying to recast the world in our model’s image. If friction—informational, transactional, contractual—is all that stands between textbook economic models and the functioning of our real economy, then there is a vocal contingent out there (“there” being mostly Silicon Valley) that sees technology as the solution. When viewed through the lens of market frictions, the much-hyped notion of the sharing economy can be seen as an effort to bring free-market salvation to bricks, mortars, and automobiles. If you’ve ever tried to hail a taxi in San Francisco or rent a room in Washington, DC, you know the frictions of which we speak. The Bay Area’s sprawl, combined with strict regulations on the cab and livery businesses, used to leave you at the mercy of the two thousand or so taxi medallion holders that covered San Francisco’s 230 square miles.
Efficiently Inefficient: How Smart Money Invests and Market Prices Are Determined by Lasse Heje Pedersen
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, mortgage debt, 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, shareholder value, Sharpe ratio, short selling, sovereign wealth fund, statistical arbitrage, statistical model, systematic trading, technology bubble, time value of money, total factor productivity, transaction costs, value at risk, Vanguard fund, yield curve, zero-coupon bond
If a country fails to invest enough, its capital stock decreases as it depreciates and becomes obsolete. One driver of investment is how low the real interest rate is, which depends in part on the inflation risk premium (i.e., stable inflation is best) and the rule of law. Also, supply shocks can arise from changes in labor-market frictions (sticky wages, search frictions, and rigid labor laws), product-market frictions (sticky prices and anticompetitive corporate measures), and capital-market frictions (market and funding illiquidity) leading to unemployment and lower capital utilization. For instance, a systemic banking crisis slows growth because the ability to finance projects is a driver of investment. In the long run, output depends on supply factors such as technological progress and population growth. 11.4.
., salaries to traders, computers, rent, legal fees, and auditors). Investors are willing to bear these costs and fees when they are outweighed by the profits that the manager is expected to extract from the efficiently inefficient market. How close are prices and returns to their fully efficient values in an efficiently inefficient market? Well, because of competition, securities’ returns net of all the relevant market frictions—transaction costs, liquidity risk, and funding costs—are very close to their fully efficient levels in the sense that consistently beating the market is extremely difficult. However, despite returns being nearly efficient, prices can deviate substantially from the present value of future cash flows. To understand this apparent paradox, note that the return to buying a cheap stock, say, depends both on the price today and the price tomorrow.
The Law of One Price breaks down when arbitrage opportunities arise in currency markets (defying the covered interest rate parity), credit markets (the CDS-bond basis), convertible bond markets, equity markets (Siamese twin stock spreads), and option markets. Investors exercise call options and convert convertible bonds before maturity and dividend payments when they need to free up cash or face large short sale costs (defying Merton’s Rule). The financial market frictions influence the real economy, and unconventional monetary policy, such as central banks’ lending facility, can be important in addressing liquidity draughts.4 TABLE I.1. PRINCIPLES OF NEOCLASSICAL FINANCE AND ECONOMICS VS. THOSE IN AN EFFICIENTLY INEFFICIENT MARKET Neoclassical Finance and Economics Efficiently Inefficient Markets Modigliani–Miller Irrelevance of capital structure Capital structure matters because of funding frictions Two-Fund Separation Everyone buys portfolios of market and cash Investors choose different portfolios depending on their individual funding constraints Capital Asset Pricing Model Expected return proportional to market risk Liquidity risk and funding constraints influence expected returns Law of One Price and Black–Scholes No arbitrage, implied derivative prices Arbitrage opportunities arise as demand pressure affects derivative prices Merton’s Rule Never exercise a call option and never convert a convertible, except at maturity/dividends Optimal early exercise and conversion free up cash, save on short sale costs, and limit transaction costs Real Business Cycles and Ricardian Equivalence Macroeconomic irrelevance of policy and finance Credit cycles and liquidity spirals driven by the interaction of macro, asset prices, and funding constraints Taylor Rule Monetary focus on interest rate policy Two monetary tools are interest rate (the cost of loans) and collateral policy (the size of loans) II.
Matchmakers: The New Economics of Multisided Platforms by David S. Evans, Richard Schmalensee
Airbnb, big-box store, business process, cashless society, Deng Xiaoping, if you build it, they will come, Internet Archive, invention of movable type, invention of the printing press, invention of the telegraph, invention of the telephone, Jean Tirole, Lyft, M-Pesa, market friction, market microstructure, mobile money, multi-sided market, Network effects, Productivity paradox, profit maximization, purchasing power parity, ride hailing / ride sharing, sharing economy, Silicon Valley, Snapchat, Steve Jobs, Tim Cook: Apple, transaction costs, two-sided market, Uber for X, Victor Gruen, winner-take-all economy
That’s the sort of problem that an important, but until recently overlooked, type of business sets out to solve by helping parties who have something valuable to exchange find each other, get together, and do a deal. Multisided Platforms In 1998, this important type of business didn’t have a name. That’s surprising, in retrospect. Many businesses had been built to reduce these sorts of market frictions, which economists tend to call transaction costs. Their basic business model had been around for thousands of years. But business schools didn’t teach classes on how to start or run businesses that help different parties get together to exchange value. Economists didn’t have a clue how these businesses worked. In fact, the companies that reduced these market frictions charged prices and adopted other strategies that economic textbooks insisted no sensible business would do. Now we call these businesses multisided platforms.2 Don’t let the economists’ unsexy name fool you.3 Multisided platforms are anything but boring.
The bigger the friction, the greater the value the platform can potentially provide, the greater the opportunity for getting participants on board, and the greater the chance for the platform to make money. Knowing which type of participants benefits the most from eliminating that friction can guide decisions on ignition strategies as well as on pricing. Sometimes, as with OpenTable, the platform drastically reduces a clear market friction, and the issue is whether the friction is big enough to enable the platform to earn adequate revenue to cover all the costs of launching and running the platform. In other cases, the platform pioneer has identified a new way for participants to interact—one that no one recognized because there was no way to do it. People and restaurants were already making and taking reservations before OpenTable came along.
Less than ten years later, in 2014, more than 84 percent of Kenyan mobile phone users, including many of the very poor, were able to use their mobile phones to transfer money to each other, to pay their bills, and to pay at stores.7 People can now also use new financial services available through their mobile money accounts to save money and take out loans, and many do.8 Increasingly, stores are accepting mobile money for payment. The way this happened in Kenya is a remarkable story of how a company figured out how to ignite a multisided platform in trying circumstances, to massively reduce important market frictions, and to provide financial services to millions of impoverished people. And it is a story of how multisided platforms—M-PESA and other mobile money schemes that have started in Kenya and elsewhere—are leapfrogging traditional industries. Kenyans don’t need to rely on banks for many financial services. And while it is too soon to tell, Kenyan merchants and consumers may end up using mobile money instead of traditional payment cards and point-of-sale equipment.
How I Became a Quant: Insights From 25 of Wall Street's Elite by Richard R. Lindsey, Barry Schachter
Albert Einstein, algorithmic trading, Andrew Wiles, Antoine Gombaud: Chevalier de Méré, asset allocation, asset-backed security, backtesting, bank run, banking crisis, Black-Scholes formula, Bonfire of the Vanities, Bretton Woods, Brownian motion, business process, buy low sell high, capital asset pricing model, centre right, collateralized debt obligation, corporate governance, correlation coefficient, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, discounted cash flows, disintermediation, diversification, 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, Nick Leeson, P = NP, pattern recognition, 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
It was a lot of fun. No data, no computer even—just pen and paper. I remember making ample use of hyperbolic tangent functions to represent the value of information without having to worry about my estimates of expected returns getting too far above the bid or below the offer. Modeling stocks in a microstructure framework, for the purpose of earning a profit, is all about modeling market frictions. Bid/offer spreads are a market friction; so is the fact that markets have to open and close and that you cannot trade in unlimited size. This was hardly sexy stuff in the early 1990s, when all the rage was customized curvature in the form of structured derivative products or over-the-counter options. At that time, quantitative finance was all about improving upon Black-Scholes. I loved being apart from the crowd.
Everything I had seen in the finance literature up to this point searched for market anomalies using closing prices or assumed continuous, single-price processes. And yet, this was not the way the world worked, I thought. Stocks trade in a double-auction framework. A trade results from someone hitting a bid, taking an offer, or two sides agreeing in the middle. So looking at how stocks moved short-term meant studying market frictions and the discreteness of how stocks moved from bid/offer to bid/offer. As far as I could tell, no one had studied this before. There was no box; so thinking out of it was all one could do. It was then I figured out how I wanted to make my mark. JWPR007-Lindsey April 30, 2007 16:14 Andrew J. Sterge 325 The story of APS seems to me a neat lesson in how quantitative finance can evolve from humble roots.
See Grinold research, difference, 35–36 scientists, 34–42 Ziff-Davis sale, 307 BASIC (computer language), 113–114 Basket options, 298 Basle CAD II, requirements, 236 Batterymarch Fellowship, establishment. See Schulman “Beating the Foreign Exchange Markets” (Sweeney), 190 Beder, Tanya Styblo, 285–294 Bedriftsøkonomusik Institutt (BI), 153–154 “Behavior of Stock Prices, The” (Fama), 266 Berman, Gregg E., 49–66 Bermudan Monte Carlo techniques, 174 Bernstein Fabozzi/Jacobs Levy Award, 192 Best practices, analysis (absence), 128 Bid/offer spreads, market friction, 325 381 Binary options (pricing), call spreads (usage), 122 Binomial trees, trinomial tree extension, 124 Blacher, Guillamume, 167 Black, Fischer, 11, 88, 172, 224 analytic software, development, 23 input, 217 Kahn visit, 44–45 Leinweber, meeting, 23 predecessor, 228 Black boxes, usage, 209 Black-Scholes and Beyond (Chriss), 124–125, 132 Black-Scholes-Merton option pricing formula, 278 Bloom, Norman, 25 Bloomberg, Mike (employ).
Reinventing the Bazaar: A Natural History of Markets by John McMillan
accounting loophole / creative accounting, Albert Einstein, Andrei Shleifer, Anton Chekhov, Asian financial crisis, congestion charging, corporate governance, crony capitalism, Dava Sobel, Deng Xiaoping, experimental economics, experimental subject, fear of failure, first-price auction, frictionless, frictionless market, George Akerlof, George Gilder, global village, Hernando de Soto, I think there is a world market for maybe five computers, income inequality, income per capita, informal economy, invisible hand, Isaac Newton, job-hopping, John Harrison: Longitude, John von Neumann, land reform, lone genius, manufacturing employment, market clearing, market design, market friction, market microstructure, means of production, Network effects, new economy, offshore financial centre, pez dispenser, pre–internet, price mechanism, profit maximization, profit motive, proxy bid, purchasing power parity, Ronald Coase, Ronald Reagan, sealed-bid auction, second-price auction, Silicon Valley, spectrum auction, Stewart Brand, The Market for Lemons, The Nature of the Firm, The Wealth of Nations by Adam Smith, trade liberalization, transaction costs, War on Poverty, Xiaogang Anhui farmers, yield management
Ronald Coase complained that the market has a “shadowy role” in economic theory, and “discussion of the market itself has entirely disappeared.” The Nobel laureates’ critique has now been addressed. Modern economics has a lot to say about the workings of markets. Theorists have opened up the black box of supply and demand and peered inside. Game theory has been brought to bear on the processes of exchange. Examining markets up close, the new economics emphasizes market frictions and how they are kept in check. In 2001, this work received recognition with the award of the Nobel Prize in economics to George Akerlof, Michael Spence, and Joseph Stiglitz for laying the foundation, as the Nobel citation said, “for a general theory of markets with asymmetric information.” Expressed in mathematics and impenetrable jargon, these new ideas reside obscurely in the technical journals.
Because of the buyers’ cost of searching, the merchants make a large profit. Big effects can come from small transaction costs. Today’s economics has the problem of information at its core. The “biggest new concept in economics in the last thirty years,” Kenneth Arrow said in 2000, “is the development of the importance of information, along with the dispersion of information.”4 Two kinds of market frictions arise from the uneven supply of information. There are search costs: the time, effort, and money spent learning what is available where for how much. And there are evaluation costs, arising from the difficulties buyers have in assessing quality. A successful market has mechanisms that hold down the costs of transacting that come from the dispersion of information. Search costs can cause markets to malfunction in large and small ways.
Firms that contract out some of their production—buying rather than making—place their trust in the market mechanism. If markets achieve such impressive efficiencies, why are so many transactions deliberately taken out of the market and put into the planned sub-economies that are firms? Why isn’t everyone an independent contractor instead of a hired employee? The answer is that firms exist as a response to market frictions. Sometimes it is less expensive to run a hierarchy than to use the market. Whether a firm produces its inputs in-house or procures them from other firms depends on the relative costs of each form of transaction. One of the factors affecting this comparison, as Ronald Coase wrote in 1937, is the efficiency with which markets work. Where the transaction costs of using the market are high, firms tend to make inputs themselves.
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, diversification, equity premium, fault tolerance, financial intermediation, fixed income, high net worth, implied volatility, index arbitrage, interest rate swap, inventory management, law of one price, Long Term Capital Management, Louis Bachelier, margin call, market friction, market microstructure, martingale, 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
Tough market conditions, an unexpected change in regulation, or terrorist events can destroy credible public companies overnight. r Transaction costs may wipe out all the profitability of stat-arb trading, particularly for investors deploying high leverage or limited capital. r The bid-ask spread may be wide enough to cancel any gains obtained from the strategy. r Finally, the pair’s performance may be determined by the sizes of the chosen stocks along with other market frictions—for example, price jumps in response to earnings announcements. Careful measurement and management of risks, however, can deliver high stat-arb profitability. Gatev, Goetzmann, and Rouwenhorst (2006) document that the out-of-sample back tests conducted on the daily equity data from 1967 to 1997 using their stat-arb strategy delivered Sharpe ratios well in excess of 4. High-frequency stat-arb delivers even higher performance numbers.
“Long-Lived Private Information and Imperfect Competition.” Journal of Finance 47, 247–270. Hollifield, B., R. Miller and P. Sandas, 2004. “Empirical Analysis of Limit Order Markets.” Review of Economic Studies 71, 1027–1063. Horner, Melchior R., 1988. “The Value of the Corporate Voting Right: Evidence from Switzerland,” Journal of Banking and Finance 12 (1), 69–84. Hou, K. and T.J. Moskowitz, 2005. “Market Frictions, Price Delay, and the CrossSection of Expected Returns.” Review of Financial Studies 18, 981–1020. References 315 Howell, M.J., 2001. “Fund Age and Performance,” Journal of Alternative Investments 4. No. 2, 57–60. Huang, R. and H. Stoll, 1997. “The Components of the Bid-ask Spread: A General Approach.” Review of Financial Studies 10, 995–1034. Huberman, G. and D. Halka, 2001. “Systematic Liquidity.”
Topics in Market Microstructure by Ilija I. Zovko
Brownian motion, continuous double auction, correlation coefficient, financial intermediation, Gini coefficient, market design, market friction, market microstructure, Murray Gell-Mann, p-value, quantitative trading / quantitative ﬁnance, random walk, stochastic process, stochastic volatility, transaction costs
Order flow and the quality of the market. In Y. Amihud, T. Ho, and R. A. Schwartz, editors, Market Making and the Changing Structure of the Securities Industry. Rowman & Littlefield, Lanham, 1985. T. E. Copeland and D. Galai. Information effects on the bid-ask spread. Journal of Finance, 38(5):1457–69, 1983. M. G. Daniels, J. D. Farmer, G. Iori, and E. Smith. Quantitative model of price diffusion and market friction based on trading as a mechanistic random process. Physical Review Letters, 90(10): Article no. 108102, 2003. H. Demsetz. The cost of transacting. The Quarterly Journal of Economics, 82:33–53, 1968. P. M. Dixon, J. Weiner, T. Mitchell-Olds, and R. Woodley. Bootstrapping the gini coefficient of inequality. Ecology, 68(5):1548– 1551, 1987. I. Domowitz and J. Wang. Auctions as algorithms: Computerized trade execution and price discovery.
Handbook of Modeling High-Frequency Data in Finance by Frederi G. Viens, Maria C. Mariani, Ionut Florescu
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
Moreover, γ (n, N ), MSEFm = MSEF + n2 α̂(n, N ) + nβ̂(n, N ) + where α̂(n, N ) and β̂(n, N ) are deﬁned in Equations (10.26) and (10.27), while γ (n, N ) := γ + 4(E[η2 ]2 + E[η4 ])(2DN ( 2π 2 2π ) − DN ( )). n n We note that if N 2 /n → 0, then lim n2 α̂(n, N ) + nβ̂(n, N ) = 0 n,N →∞ and lim n,N →∞ γ (n, N ) = 8E[η2 ]IV + 2E[η4 ] + 6E[η2 ]2 . (10.29) It follows that the MSE of the Fourier estimator does not diverge, and it is not signiﬁcantly affected by microstructure noise; in fact, by conveniently choosing N , we obtain that MSEF and MSEFm differ by the positive constant term (Eq. 10.29). We conclude that the Fourier estimator needs no correction in order to be asymptotically unbiased and robust to market frictions of MA(1)-type, that is, the microstructure noise is represented by independent identically distributed random variables. The result is generalized to noise correlated with the efﬁcient returns in Mancino and Sanfelici (2008). 10.3.2 MONTE CARLO ANALYSIS The theoretical results above can be reproduced by simulating discrete data from a continuous time stochastic volatility model with microstructure noise as in Mancino and Sanfelici (2008).
Using high-frequency data in dynamic portfolio choice. Economet Rev 2008;27/1-3:163–198. Barndorff-Nielsen OE, Graversen SE, Jacod J, Shephard N. Limit theorems for bipower variation in ﬁnancial econometrics. Economet Theor 2006;22(4):677–719. Barndorff-Nielsen OE, Hansen PR, Lunde A, Shephard N. Realized kernels can consistently estimate integrated variance: correcting realized variance for the effect of market frictions. Working paper, 2005. Barndorff-Nielsen OE, Hansen PR, Lunde A, Shephard N. Designing realized kernels to measure the ex-post variation of equity prices in the presence of noise. Econometrica 2008;76/6:1481–1536. Barndorff-Nielsen OE, Hansen PR, Lunde A, Shephard N. Multivariate realized kernels: consistent positive semi-deﬁnite estimators of the covariation of equity prices with noise and non-synchronous trading.
Capitalism and Freedom by Milton Friedman
affirmative action, Berlin Wall, central bank independence, Corn Laws, Deng Xiaoping, floating exchange rates, Fractional reserve banking, full employment, invisible hand, Joseph Schumpeter, liquidity trap, market friction, minimum wage unemployment, price discrimination, rent control, road to serfdom, Ronald Reagan, secular stagnation, Simon Kuznets, the market place, The Wealth of Nations by Adam Smith, union organizing
The potential gains, particularly to early entrants, are so great that it would be worth incurring extremely heavy administrative costs.10 Whatever the reason, an imperfection of the market has led to underinvestment in human capital. Government intervention might therefore be rationalized on grounds both of “technical monopoly,” insofar as the obstacle to the development of such investment has been administrative costs, and of improving the operation of the market, insofar as it has been simply market frictions and rigidities. If government does intervene, how should it do so? One obvious form of intervention, and the only form that has so far been taken, is outright government subsidy of vocational or professional schooling financed out of general revenues. This form seems clearly inappropriate. Investment should be carried to the point at which the extra return repays the investment and yields the market rate of interest on it.
barriers to entry, conceptual framework, correlation coefficient, discrete time, disintermediation, distributed generation, experimental economics, financial intermediation, index arbitrage, interest rate swap, inventory management, market clearing, market design, market friction, market microstructure, martingale, price discovery process, price discrimination, quantitative trading / quantitative ﬁnance, random walk, Richard Thaler, second-price auction, short selling, statistical model, stochastic process, stochastic volatility, transaction costs, two-sided market, ultimatum game
At this point, the dealer revises her quotes to $109 bid, offered at $111 (thus bracketing the new value). Each of the other 99 customers will perceive an opportunity cost of $10 (=$110 − $100) and may well attribute this to sloth on the part of their brokers or their systems. Thus, the aggregate opportunity cost is $990, for an aggregate implementation shortfall of $991. It is nonsensical, of course, to suggest that aggregate welfare could be enhanced by this amount if market frictions or broker ineptitude were eliminated. The problem is that the benchmark price of π0 = $100 does not come close, given the new information, to clearing the market. The profits realized by the lucky first trader are akin to lottery winnings. Individual traders might attempt to gain advantage by increasing the speed of their order submission linkages, but because only one trader can arrive first, the situation is fundamentally a tournament (in the economic sense). 14.2.1 The Implementation Cost for Liquidity Suppliers Is implementation cost a useful criterion for liquidity suppliers?
Andrei Shleifer, asset allocation, capital asset pricing model, correlation coefficient, cross-subsidies, Daniel Kahneman / Amos Tversky, diversified portfolio, endowment effect, index arbitrage, index fund, locking in a profit, Long Term Capital Management, loss aversion, margin call, market friction, market microstructure, mental accounting, merger arbitrage, new economy, prediction markets, price stability, profit motive, random walk, Richard Thaler, risk-adjusted returns, risk/return, Sharpe ratio, short selling, transaction costs, Vanguard fund
First, it is not clear that those mispricings actually occur, given the noise in estimates. Second, trading strategies are not easily amenable to long holding periods. Short-term price patterns considered here are of two kinds: the pattern could be a form of price drift, where the price continues to move in the same direction, or it could be a price reversal where the 56 Short-Term Price Drift price moves in the opposite direction. These price patterns may be due to market frictions, a result of market inefficiency, or related to information arrival. The earliest documentation of short-term price drift is related to earnings announcements, in which it was found that firms with surprisingly good earnings earn abnormal returns of about 2 percent in the following three months, whereas firms with surprisingly bad earnings lose abnormally. Evidence of price drift suggests that information in the earnings announcement is not immediately and fully reflected in prices.
Market Risk Analysis, Quantitative Methods in Finance by Carol Alexander
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, 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, transaction costs, value at risk, volatility smile, Wiener process, yield curve
Now in place of (I.3.141) we write dXt = − Xtdt + dBt (I.3.142) The parameter is called the rate of mean reversion and the parameter is called the long term value of X. In Section II.5.3.7 we prove that the discrete time version of (I.3.142) is a stationary AR(1) model. I.3.7.3 Stochastic Models for Asset Prices and Returns Time series of asset prices behave quite differently from time series of returns. In efficient markets a time series of prices or log prices will follow a random walk. More generally, even in the presence of market frictions and inefficiencies, prices and log prices of tradable assets are integrated stochastic processes. These are fundamentally different from the associated returns, which are generated by stationary stochastic processes. Figures I.3.28 and I.3.29 illustrate the fact that prices and returns are generated by very different types of stochastic process. Figure I.3.28 shows time series of daily prices (lefthand scale) and log prices (right-hand scale) of the Dow Jones Industrial Average (DJIA) DJIA 12000 9.4 Log DJIA 9.3 11000 9.2 10000 9.1 9000 9 8000 8.9 Sep-01 May-01 Jan-01 Sep-00 May-00 Jan-00 Sep-99 May-99 Jan-99 Sep-98 May-98 8.8 Jan-98 7000 Figure I.3.28 Daily prices and log prices of DJIA index 56 This is not the only possible discretization of a continuous increment.
The Euro: How a Common Currency Threatens the Future of Europe by Joseph E. Stiglitz, Alex Hyde-White
bank run, banking crisis, barriers to entry, battle of ideas, Berlin Wall, Bretton Woods, capital controls, Carmen Reinhart, cashless society, central bank independence, centre right, cognitive dissonance, collapse of Lehman Brothers, collective bargaining, corporate governance, correlation does not imply causation, credit crunch, Credit Default Swap, currency peg, dark matter, David Ricardo: comparative advantage, disintermediation, diversified portfolio, eurozone crisis, Fall of the Berlin Wall, fiat currency, financial innovation, full employment, George Akerlof, Gini coefficient, global supply chain, Growth in a Time of Debt, housing crisis, income inequality, incomplete markets, inflation targeting, investor state dispute settlement, invisible hand, Kenneth Rogoff, knowledge economy, labour market flexibility, labour mobility, manufacturing employment, market bubble, market friction, market fundamentalism, Martin Wolf, Mexican peso crisis / tequila crisis, moral hazard, mortgage debt, neoliberal agenda, new economy, open economy, paradox of thrift, pension reform, pensions crisis, price stability, profit maximization, purchasing power parity, quantitative easing, race to the bottom, risk-adjusted returns, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Reagan, savings glut, secular stagnation, Silicon Valley, sovereign wealth fund, the payments system, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, transfer pricing, trickle-down economics, Washington Consensus, working-age population
Since the start of the euro, it continues as what is sometimes called ERM II, a band linking the Danish krone to the euro. 37 Though the basic idea of full employment is clear—that everyone who would like a job can get one at the prevailing wages for those with the individual’s skills and talents—there is some controversy over the precise definition of full employment. The general notion is that the labor market is just sufficiently loose—with job seekers matching employers looking for employees—that there is no inflationary pressure. Because of labor market frictions—it takes time to find a good match between employers and employees—this “natural rate” is greater than zero, normally around 2 to 3 percent. Unemployment might also exist because of rigidities in the adjustment of relative wages—the labor market for skilled labor might be so tight that wages are rising, but there may still be unemployment of unskilled workers. This level of unemployment is sometimes referred to as structural unemployment.
Valuation: Measuring and Managing the Value of Companies by Tim Koller, McKinsey, Company Inc., Marc Goedhart, David Wessels, Barbara Schwimmer, Franziska Manoury
air freight, barriers to entry, Basel III, BRICs, business climate, business process, capital asset pricing model, capital controls, cloud computing, compound rate of return, conceptual framework, corporate governance, corporate social responsibility, credit crunch, Credit Default Swap, discounted cash flows, distributed generation, diversified portfolio, energy security, equity premium, index fund, iterative process, Long Term Capital Management, market bubble, market friction, meta analysis, meta-analysis, new economy, p-value, performance metric, Ponzi scheme, price anchoring, purchasing power parity, quantitative easing, risk/return, Robert Shiller, Robert Shiller, shareholder value, six sigma, sovereign wealth fund, speech recognition, technology bubble, time value of money, too big to fail, transaction costs, transfer pricing, value at risk, yield curve, zero-coupon bond
But some managers and academics claim that the lower price should make the stock more attractive for capital-constrained investors, thereby increasing demand, improving liquidity, and leading to higher returns for shareholders.41 In many cases, a stock split is indeed accompanied by positive abnormal returns to shareholders (see Exhibit 5.16).42 The abnormal returns have nothing to do with the split as such but are simply a function of self-selection and signaling. Self-selection is the tendency of companies to split their stocks into lower denominations because of a prolonged rise in their share price, as shown in Exhibit 5.16. As a result, one should expect any sample of companies that 40 R. D. Boehme and B. R. Danielsen report over 6,000 stock splits between 1950 and 2000: “Stock-Split Post-Announcement Returns: Underreaction or Market Friction?” Financial Review 42 (2007): 485–506. D. Ikenberry and S. Ramnath report over 3,000 stock splits between 1988 and 1998: “Underreaction to Self-Selected News Events: The Case of Stock Splits,” Review of Financial Studies 15 (2002): 489–526. 41 There is ample evidence to show that this is not the case: after a split, trading volumes typically decline, and brokerage fees and bid-ask spreads increase, indicating lower liquidity, if anything.