Investor Sentiment in the Stock Market

Real investors and markets are too complicated to be neatly summarized by a few selected biases and trading frictions. The “top down” approach to behavioral finance focuses on the measurement of reduced form, aggregate sentiment and traces its effects to stock returns. It builds on the two broader and more irrefutable assumptions of behavioral finance—sentiment and the limits to arbitrage—to explain which stocks are likely to be most affected by sentiment. In particular, stocks of low capitalization, younger, unprofitable, high volatility, non-dividend paying, growth companies, or stocks of firms in financial distress, are likely to be disproportionately sensitive to broad waves of investor sentiment. We review the theoretical and empirical evidence for these predictions. Malcolm Baker is Associate Professor of Finance, Harvard Business School, Boston, Massachusetts. Jeffrey Wurgler is Associate Professor of Finance, Stern School of Business, New York University, New York, New York. Both authors are Faculty Research Fellows, National Bureau of Economic Research, Cambridge, Massachusetts. Their e-mail addresses are and , respectively. The history of the stock market is full of events striking enough to earn their own names: the Great Crash of 1929, the 'Tronics Boom of the early 1960s, the Go-Go Years of the late 1960s, the Nifty Fifty bubble of the early 1970s, and the Black Monday crash of October 1987. Each of these events refers to a dramatic level or change in stock prices that seems to defy explanation. The standard finance model, where unemotional investors always force capital market prices to equal to the rational present value of expected future cash flows, has considerably difficulty fitting these patterns. Researchers in behavioral finance have been working to augment the standard model with an alternative model built on two basic assumptions. The first assumption is that investors are subject to sentiment. Investor sentiment, defined broadly, is a belief about future cash flows and investment risks that is not justified by the facts at hand. The second assumption is that betting against sentimental investors is costly and risky. And so, rational investors, or arbitrageurs as they are often called, are not as aggressive in forcing prices to fundamentals as the standard model would suggest. In the language of modern behavioral finance, there are limits to arbitrage. Recent stock market history has cooperated nicely, providing the Internet bubble and the ensuing Nasdaq and telecom crashes and thus validating the two premises of behavioral finance. A period of extraordinary investor sentiment pushed the prices of speculative and difficult-to-value technology stocks to unfathomable levels in the late 1990s. Instead of creating opportunity for contrarian arbitrageurs, the period forced many out of business, as prices that were merely high went higher still before an eventual crash. Now, the question is no longer, as it was a few decades ago, whether investor sentiment affects stock prices, but rather how to measure investor sentiment and quantify its effects. One 1 See De Long et al. (1990) and Shleifer and Vishny (1997) for this conception.