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160
Why Bounded Rationality
 Journal of Economic Literature
, 1996
"... Rothschild, and three most helpful referees. Very special thanks for many years of helpful insights are due to Richard Day and Luigi Ermini. Hamlet: “What a piece of work is a man! how noble in reason! how infinite in faculties!” ..."
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Cited by 205 (0 self)
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Rothschild, and three most helpful referees. Very special thanks for many years of helpful insights are due to Richard Day and Luigi Ermini. Hamlet: “What a piece of work is a man! how noble in reason! how infinite in faculties!”
Empirical properties of asset returns: stylized facts and statistical issues
 Quantitative Finance
, 2001
"... We present a set of stylized empirical facts emerging from the statistical analysis of price variations in various types of financial markets. We first discuss some general issues common to all statistical studies of financial time series. Various statistical properties of asset returns are then des ..."
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Cited by 149 (2 self)
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We present a set of stylized empirical facts emerging from the statistical analysis of price variations in various types of financial markets. We first discuss some general issues common to all statistical studies of financial time series. Various statistical properties of asset returns are then described: distributional properties, tail properties and extreme fluctuations, pathwise regularity, linear and nonlinear dependence of returns in time and across stocks. Our description emphasizes properties common to a wide variety of markets and instruments. We then show how these statistical properties invalidate many of the common statistical approaches used to study financial data sets and examine some of the statistical problems encountered in each case.
The Equity Premium
 Journal of Finance
, 2002
"... We estimate the equity premium using dividend and earnings growth rates to measure the expected rate of capital gain. Our estimates for 1951 to 2000, 2.55 percent and 4.32 percent, are much lower than the equity premium produced by the average stock return, 7.43 percent. Our evidence suggests that t ..."
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Cited by 111 (3 self)
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We estimate the equity premium using dividend and earnings growth rates to measure the expected rate of capital gain. Our estimates for 1951 to 2000, 2.55 percent and 4.32 percent, are much lower than the equity premium produced by the average stock return, 7.43 percent. Our evidence suggests that the high average return for 1951 to 2000 is due to a decline in discount rates that produces a large unexpected capital gain. Our main conclusion is that the average stock return of the last halfcentury is a lot higher than expected.
Speculation Duopoly with Agreement to Disagree: Can Overconfidence Survive the Market Test?
 Journal of Finance
, 1997
"... In a duopoly model of informed speculation, we show that overconfidence may strictly dominate rationality since an overconfident trader may not only generate higher expected profit and utility than his rational opponent, but also higher than if he were also rational. This occurs because overconfiden ..."
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Cited by 107 (1 self)
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In a duopoly model of informed speculation, we show that overconfidence may strictly dominate rationality since an overconfident trader may not only generate higher expected profit and utility than his rational opponent, but also higher than if he were also rational. This occurs because overconfidence acts like a commitment device in a standard Cournot duopoly. As a result, for some parameter values the Nash equilibrium of a twofund game is a Prisoner's Dilemma in which both funds hire overconfident managers. Thus, overconfidence can persist and survive in the long run. 2 The rational expectations hypothesis implies that economic agents make decisions as though they know a correct probability distribution of the underlying uncertainty. According to the traditional view (Alchian (1950) and Friedman (1953)), the rational expectations hypothesis is empirically plausible because rational beliefs are better able to survive the market test than irrational beliefs. Yet, the empirical liter...
Dynamic consumption and portfolio choice with stochastic volatility in incomplete markets
, 2003
"... ..."
A catering theory of dividends
 JOURNAL OF FINANCE
, 2002
"... We develop a theory in which the decision to pay dividends is driven by investor demand. Managers cater to investors by paying dividends when investors put a stock price premium on payers and not paying when investors prefer nonpayers. To test this prediction, we construct four time series measures ..."
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Cited by 55 (16 self)
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We develop a theory in which the decision to pay dividends is driven by investor demand. Managers cater to investors by paying dividends when investors put a stock price premium on payers and not paying when investors prefer nonpayers. To test this prediction, we construct four time series measures of the investor demand for dividend payers. By each measure, nonpayers initiate dividends when demand for payers is high. By some measures, payers omit dividends when demand is low. Further analysis confirms that the results are better explained by the catering theory than other theories of dividends.
why stock market crash
, 2003
"... Abstract: The young science of complexity, which studies systems as diverse as the human body, the earth and the universe, offers novel insights on the question raised in the title. The science of complexity explains largescale collective behavior, such as wellfunctioning capitalistic markets, and ..."
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Cited by 51 (11 self)
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Abstract: The young science of complexity, which studies systems as diverse as the human body, the earth and the universe, offers novel insights on the question raised in the title. The science of complexity explains largescale collective behavior, such as wellfunctioning capitalistic markets, and also predicts that financial crashes and depressions are intrinsic properties resulting from the repeated nonlinear interactions between investors. Applying concepts and methods from complex theory and statistical physics, we have developed mathematical measures to successfully predict the emergence and development of speculative bubbles as well as depressions. This essay attempts to capture and extend the essence of the book with the same title published in January 2003 by Princeton University Press. Recent novelties and live predictions are available at
Herd Behavior and Aggregate Fluctuations in Financial Markets
"... We present a simple model of a stock market where a random communication structure between agents generically gives rise to heavy tails in the distribution of stock price variations in the form of an exponentially truncated powerlaw, similar to distributions observed in recent empirical studies of ..."
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Cited by 50 (1 self)
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We present a simple model of a stock market where a random communication structure between agents generically gives rise to heavy tails in the distribution of stock price variations in the form of an exponentially truncated powerlaw, similar to distributions observed in recent empirical studies of high frequency market data. Our model provides a link between two wellknown market phenomena: the heavy tails observed in the distribution of stock market returns on one hand and 'herding' behavior in financial markets on the other hand. In particular, our study suggests a relation between the excess kurtosis observed in asset returns, the market order flow and the tendency of market participants to imitate each other. Keywords: heavy tails, financial markets, herd behavior, market organization, intermittency, random graphs, percolation. JEL Classification number: C0, D49, G19 1 R. Cont gratefully acknowledges an AMX fellowship from Ecole Polytechnique (France) and thanks Science & Financ...
Dynamic Asset Allocation under Inflation
 Journal of Finance
, 2002
"... Wachter, two anonymous referees, and participants at the Brown Bag Micro Finance Lunch Seminar at the Wharton ..."
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Cited by 43 (2 self)
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Wachter, two anonymous referees, and participants at the Brown Bag Micro Finance Lunch Seminar at the Wharton
Crashes as Critical Points
 International Journal of Theoretical and Applied Finance
, 2000
"... We study a rational expectation model of bubbles and crashes. The model has two components: (1) our key assumption is that a crash may be caused by local selfreinforcing imitation between noise traders. If the tendency for noise traders to imitate their nearest neighbors increases up to a certain p ..."
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Cited by 40 (19 self)
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We study a rational expectation model of bubbles and crashes. The model has two components: (1) our key assumption is that a crash may be caused by local selfreinforcing imitation between noise traders. If the tendency for noise traders to imitate their nearest neighbors increases up to a certain point called the “critical ” point, all noise traders may place the same order (sell) at the same time, thus causing a crash. The interplay between the progressive strengthening of imitation and the ubiquity of noise is characterized by the hazard rate, i.e. the probability per unit time that the crash will happen in the next instant if it has not happened yet. (2) Since the crash is not a certain deterministic outcome of the bubble, it remains rational for traders to remain invested provided they are compensated by a higher rate of growth of the bubble for taking the risk of a crash. Our model distinguishes between the end of the bubble and the time of the crash: the rational expectation constraint has the specific implication that the date of the crash must be random. The theoretical death of the bubble is not the time of the crash because the crash could happen at any time before, even though this is not very likely. The death of the bubble is the most probable time for the crash. There also exists a finite probability of attaining the end of the bubble without crash. Our model has specific predictions about the presence of certain critical logperiodic patterns in precrash prices, associated with the deterministic components of the bubble mechanism. We provide empirical evidence showing that these patterns were indeed present before the crashes of 1929, 1962 and 1987 on Wall Street and the 1997 crash on the Hong Kong Stock Exchange. These results are compared with statistical tests on synthetic data. 1