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Overconfidence, Predictable Returns, And Excessive Trading

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Overconfidence, Predictable Returns, And Excessive Trading

Kent D. Daniel

Columbia Business School – Finance and Economics; National Bureau of Economic Research (NBER)

David A. Hirshleifer

University of California, Irvine – Paul Merage School of Business

October 20, 2015

Journal of Economic Perspectives, Volume 29, Number 4, Fall 2015


Individuals and asset managers trade aggressively, resulting in high volume in asset markets, even when such trading results in high risk and low net returns. Asset prices display patterns of predictability that are difficult to reconcile with rational expectations – based theories of price formation. This paper discusses how investor overconfidence can explain these and other stylized facts. We review the evidence from psychology and securities markets bearing upon overconfidence effects, and present a set of overconfidence-based models that are consistent with this evidence.

Overconfidence, Predictable Returns, And Excessive Trading – Introduction

The last several decades have seen a shift away from a fully rational paradigm of financial markets towards one in which investor behavior is influenced by psychological biases. One of the main factors contributing to this evolution is a body of evidence showing how psychological bias affects the behavior of economic actors. Another main factor is an accumulation of evidence that is hard to reconcile with fully rational models of security market trading volumes and returns. In particular, asset markets exhibit trading volumes that are high, while individuals and asset managers trade aggressively, even when such trading results in high risk and low net returns. Moreover, asset prices display patterns of predictability that are difficult to reconcile with rational expectations based theories of price formation.

In this paper, we discuss the role of overconfidence as an explanation for these patterns. Overconfidence means having mistaken valuations and believing in them too strongly. It might seem that actors in liquid financial markets should not be very susceptible to overconfidence, because return outcomes are measurable, providing extensive feedback. However, overconfidence has been documented among experts and professionals, including those in the finance profession. For example, overconfidence is observed among corporate financial officers (Ben-David, Graham and Harvey 2013) and among professional traders and investment bankers (Glaser, Langer and Weber 2013). People tend to be overoptimistic about their life prospects (Weinstein 1980), and this optimism directly affects their financial decisions (Puri and Robinson 2007).

We do not mean to suggest that overconfidence is the only phenomenon worth considering in behavioral finance, nor that it should serve as an all-purpose explanation for all financial anomalies. But overconfidence seems likely to be a key factor in financial decision making. Overconfidence is a widespread psychological phenomenon (as discussed by Malmendier and Taylor in their overview for this symposium), and is associated with a cluster of related effects. For example, it includes overplacement – overestimation of one’s rank in a population on some positive dimension – and overprecision – overestimation of the accuracy of one’s beliefs. An example is overestimation of one’s ability to predict the stock market’s future returns. A cognitive process that helps support overconfident beliefs is self-attribution bias, in which people give credit their own talents and abilities for past successes, while blaming their failures on bad luck.

To evaluate the importance of overconfidence for financial markets, we proceed as follows. We start by reviewing two of the primary financial market anomalies at odds with rational agent asset pricing theories: the arguments that trading volumes are excessive and the evidence that security returns are in some ways predictable. We then sketch a sequence of models of investor trading and security prices that include various aspects of overconfidence, with increasing complexity, and discuss the empirical implications of each of these models. We hope that this presentation will clarify which aspects of the model are important in delivering specific empirical implications. Finally, we offer some conclusions about how overconfidence contributes to our understanding of financial markets.


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