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Herd Behavior in Efficient Financial Markets

Abstract

Rational herd behavior and informationally efficient security prices have long been considered to be mutually exclusive but for exceptional cases. In this paper we describe conditions on the underlying information structure that are necessary and sufficient for informational herding. Employing a standard sequential security trading model, we argue that people may be subject to herding if and only if there is sufficient amount of noise and, loosely, their information leads them to believe that extreme outcomes are more likely than moderate ones. We then show that herding has a significant effect on prices: prices can move substantially during herding and they become more volatile than if there were no herding. Furthermore, herding can be persistent and can affect the process of learning. We also characterize conditions for contrarian behavior. Our analysis suggests that herding (and contrarian behavior) may be more pervasive than was originally thought. Hence, the paper provides a new perspective on herding in financial markets with efficient pricesMicrostructure, Sequential Trades, Herding, Monotone Likelihood

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