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The efficient markets hypothesis has been the central proposition in finance for nearly thirty years. It states that securities prices in financial markets must equal fundamental values, either because all investors are rational or because arbitrage eliminates pricing anomalies.
This book describes an alternative approach to the study of financial markets: behavioral finance. This approach starts with an observation that the assumptions of investor rationality and perfect arbitrage are overwhelmingly contradicted by both psychological and institutional evidence. In actual financial markets, less than fully rational investors trade against arbitrageurs whose resources are limited by risk aversion, short horizons, and agency problems. The book presents and empirically
evaluates models of such inefficient markets.
Behavioral finance models both explain the available financial data better than does the efficient markets hypothesis and generate new empirical predictions. These models can account for such anomalies as the superior performance of value stocks, the closed end fund puzzle, the high returns on stocks included in market indices, the persistence of stock price bubbles, and even the collapse of several well-known hedge funds in 1998. By summarizing and expanding the research in behavioral finance,
the book builds a new theoretical and empirical foundation for the economic analysis of real-world markets.
- Sales Rank: #798436 in eBooks
- Published on: 2000-03-09
- Released on: 2000-03-09
- Format: Kindle eBook
Review
"An excellent academic discussion of [stock mispricing] and other behavioral influences in the stock market."--Jeff Madrick, New York Review of Books
"The only advanced undergraduate or graduate text available on the subject."--Jeffrey Wurgler, Yale School of Management
Review
"An excellent academic discussion of [stock mispricing] and other behavioral influences in the stock market."--Jeff Madrick, New York Review of Books
"The only advanced undergraduate or graduate text available on the subject."--Jeffrey Wurgler, Yale School of Management
About the Author
Andrei Shleifer is professor of Economics at Harvard University.
Most helpful customer reviews
24 of 29 people found the following review helpful.
Necessary Book for Finance
By W. James D. Easton
The material in this book is necessary for anyone who is responsible for managing money or involved with a business entity doing trading in financial markets. Increasingly this is "everyone."
The good news is that the conclusions and punchlines are presented clearly and simply. A person who does not want to follow the math (there is a lot of it) can skip to the arguments and conclusions and get an enormous amount of valuable information. The bad news is that little effort has been expended to make the math attractive. A person wishing to slog through the math will have to be prepared to sit down with pencil & paper & patience. Some editing by someone who cared would have made this book much more attractive to the average student. Martin Baxter & Andrew Rennie's "Financial Calculus" gives a good example of how this can be done.
1 of 1 people found the following review helpful.
Best introductory book on behavioral finance
By Robert Stephenson-padron
As has been admitted by even the staunchest former proponents of financial economics (such as Burton Malkiel), the multi-decades old dominant intellectual field in academic finance has piled up against itself persistent anomalous data. Thus, it is no surprise, as the science of economics advanced, that a new intellectual field would develop to challenge and replace the old. Behavioral finance, which relaxes some of the key assumptions in financial economics, utilizes survey data, and integrates knowledge from psychology to better understand financial markets, is that new intellectual field.
Although still controversial, young economists and financial professionals should become versed in this new field as early as possible: 1) because there is huge room for new research where creative economists can flex their muscle and 2) financial professionals that drop the old adherence to financial economics will have an edge over those that don't. Andrei Shleifer's work is the best introductory work on behavioral finance that I've come across, and I thus strongly recommend it to those who want a quick and easy to understand introduction to this field which is the wave of the future of academic finance (well, I hope).
Robert Stephenson-Padron
MSc student (economics & finance)
University of Navarra, Spain
58 of 60 people found the following review helpful.
chapter by chapter critique
By Eric Falkenstein
Chapter 1 lays out the two pillars to his argument: a theory of investor sentiment, and limits to arbitrage. Both are needed, as without systematic deviations from rationality, irrational decisions cancel each other out, making them somewhat uninteresting (excepting increasing volume); without limits to arbitrage such irrational deviations from `true value' are instantly poached by savvy rational investors.
The first model shows that if arbitrage is limited and noise traders have systematic biases, prices can deviate from fundamental value (DeLong et al, 1990a). That is, Shell can deviate from its fundamental value because no one has enough money and time to put the price into equilibrium, and investor sentiment varies between markets and over time. This model also has the interesting implication that less informed investors might earn a higher rate of return on their total portfolios because they irrationally believe they have a more favorable risk-return opportunity and hence invest in securities with a higher return. In effect, their stupidity effectively diminishes their risk aversion, and in the long run allows a lucky few of them to reap the financial rewards that would accrue to the less risk averse (one could call it the `Forrest Gump' effect). As opposed to speculation weeding out the irrational traders and making only the best opinions matter, the irrational can dominate.
The closed fund puzzle is presented in chapter three and highlights some of the problems of this approach (Lee, Thaler and Shleifer, 1991). The issue to be explained is why 1) funds are issued at premiums to net asset value (overpriced) and 2) funds eventually trade at discount to net asset value (underpriced). While the underpricing is addressed through the mechanism outlined in the first model (limited arbitrage and noise traders), the overpricing effect is addressed by assuming that `noise traders' buy up the initial issuance-not very subtle. Clearly if noise traders can be foisted into overpaying or underpaying within models by assumption, it is hard to avoid the inference that this approach can explain everything and thus nothing.
Of course on occasion EMH proponents also try to explain seemingly everything, where exceptions are assumed order-statistics until they are granted statistical significance, at which time they are instantly seen as an efficient proxy of unmeasured risk (e.g., the value and size effect). Yet explanatory greediness is clearly more of a problem to the inefficient markets camp. For example, in addition to the above example, investor sentiment is used to explain both the equity-premium puzzle (i.e., why stock prices are too low on average) and why recent p/e multiples are too high (page 180): if the equity-premium is a `puzzle' it is difficult to also say that our currently historically high p/e multiple is irrational, but if the p/e ratio `should' be lower (around 15) then the equity premium is not a puzzle.
In chapter 4 a nice approach is taken towards professional arbitrage (Shleifer and Vishny, 1997). By modeling it as a principal agent problem, this model captures some relevant issues usually addressed by the Industrial Organization literature. Clearly there is relevance to modeling the situation where hedge fund managers have uncertain skill and investors have to evaluate them. The failure of famed hedge fund LTCM in 1998 was defended, like almost all bankruptcies, as a failure of investor's patience--outsiders are always much quicker at pulling the plug than insiders would prefer. Modeling, in this case, a liquidity constraint, is a highly relevant issue that seems well suited for asymmetric information and principal-agent modeling.
Chapter 5 introduces the model of investor sentiment, that is, why we should expect noise traders to vary systematically in their buy or sell orders (Barberis, Shleifer, and Vishny, 1998). It derives a straightforward and testable hypothesis based on Bayesian updating of a regime-switching model. For earnings or other surprises that continue a trend, overreaction is predicted, for surprises that counter a trend, underreaction is predicted.
In chapter 6, we see the DeLong, Shleifer, Summers, and Waldeman series on noise traders and positive feedback loops (DSSW, 1990b). This sort of model bothers me because it is a bit disingenuous. It puts superficial rigor onto to the simple idea that "given constraints on arbitrage, irrational trend-following investors can make it rational to follow trends, and thus rational traders can be destabilizing." It is not a compelling model because the results are not derived inevitably and subtly from general assumptions and a friction, but instead from assumptions which guarantee the result (e.g., trend-following noise traders and limited arbitrage). Is it at all helpful to take a straightforward idea that can be clearly expressed in a sentence and model this with contrived algebra? Personally I do not think so, though the realist in me understands that without a model to point to, the idea would not be taken as seriously as it has.
It is stressed throughout the book that risky arbitrage makes taking advantage of pervasive irrationality difficult. Yet if irrationality is a systemic and pervasive phenomenon, then there exist hundreds of scenarios like mispriced Shell, overvalued Amazon, undepriced closed funds, overvalued currencies, overvalued IPOs, etc. Surely over several years these positions, somewhat independent, should make significant abnormal risk-adjusted returns. As is more probable, there are not hundreds of such situations, but perhaps a handful, and with the rational markets assumption ignored hundreds more opportunities appear to exist but actually do not (e.g., the small firm effect). Be sure to monitor Thaler's funds (UBRLX and UBVLX) and Sheifer's fund (LSVEX).
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