Recent empirical research in finance has uncovered two families of pervasive regularities: underreaction of stock prices to news such as earnings announcements, and overreaction of stock prices to a series of good or bad news. In this paper, we present a parsimonious model of investor sentiment, or of how investors form beliefs, which is consistent with the empirical findings. The model is based on psychological evidence and produces both underreaction and overreaction for a wide range of parameter values.

ABSTRACT We investigate whether prospect theory preferences can predict a disposition effect. We consider two implementations of prospect theory: in one case, preferences are defined over annual gains and losses; in the other, they are defined over realized gains and losses. Surprisingly, the annual gain/loss model often fails to predict a disposition effect. The realized gain/loss model, however, predicts a disposition effect more reliably. Utility from realized gains and losses may therefore be a useful way of thinking about certain aspects of individual investor trading.

We argue that “narrow framing, ” whereby an agent who is offered a new gamble evaluates that gamble in isolation, may be a more important feature of decisionmaking than previously realized. Our starting point is the evidence that people are often averse to a small, independent gamble, even when the gamble is actuarially favorable. We find that a surprisingly wide range of utility functions, including many nonexpected utility specifications, have trouble explaining this evidence, but that this difficulty can be overcome by allowing for narrow framing. Our analysis makes predictions as to what kinds of preferences can most easily address the stock market participation puzzle. (JEL D81, G11) Economists, and financial economists in particular, have long been interested in how people evaluate risk. In this paper, we try to shed new light on this topic. Specifically, we argue that a feature known as “narrow framing ” may play a more important role in decision-making under

We present an extrapolative model of bubbles. In the model, many investors form their demand for a risky asset by weighing two signals—an average of the asset’s past price changes and the asset’s degree of overvaluation—and “waver” over time in the relative weight they put on them. The model predicts that good news about fundamentals can trigger large price bubbles, that bubbles will be accompanied by high trading volume, and that volume increases with past asset returns. We present empirical evidence that bears on some of the model’s distinctive predictions.

Survey evidence suggests that many investors form beliefs about future stock market returns by extrapolating past returns. Such beliefs are hard to reconcile with existing models of the aggregate stock market. We study a consumption-based asset pricing model in which some investors form beliefs about future price changes in the stock market by extrapolating past price changes, while other investors hold fully rational beliefs. We find that the model captures many features of actual prices and returns; importantly, however, it is also consistent with the survey evidence on investor expectations.

We argue that “narrow framing,” whereby an agent who is offered a new gamble evaluates that gamble in isolation, may be a more important feature of decision-making than previously realized. Our starting point is the evidence that people are often averse to a small, independent gamble, even when the gamble is actuarially favorable. We find that a surprisingly wide range of utility functions, including many nonexpected utility specifications, have trouble explaining this evidence, but that this difficulty can be overcome by allowing for narrow framing. Our analysis makes predictions as to what kinds of preferences can most easily address the stock market participation puzzle.

ABSTRACT We present a new model of asset prices in which investors evaluate risk according to prospect theory and examine its ability to explain 23 prominent stock market anomalies. The model incorporates all of the elements of prospect theory, accounts for investors' prior gains and losses, and makes quantitative predictions about an asset's average return based on empirical estimates of the asset's return volatility, return skewness, and past capital gain. We find that the model can help explain a majority of the 23 anomalies.

We test the hypothesis that, when thinking about allocating money to a stock, investors mentally represent the stock by the distribution of its past returns and then evaluate this distribution in the way described by prospect theory. In a simple model of asset prices in which some investors think in this way, a stock whose past return distribution has a high (low) prospect theory value earns a low (high) subsequent return, on average. We find empirical support for this prediction in the cross-section of stock returns in the U.S. market, and also in a majority of forty-six other national stock markets. ( JEL D03) Received November 19, 2014; accepted May 20, 2016, by Editor Stefan Nagel.

We use measures of neural activity provided by functional magnetic resonance imaging (fMRI) to test the "realization utility" theory of investor behavior, which posits that people derive utility directly from the act of realizing gains and losses. Subjects traded stocks in an experimental market while we measured their brain activity. We find that all subjects exhibit a strong disposition effect in their trading, even though it is suboptimal. Consistent with the realization utility explanation for this behavior, we find that activity in the ventromedial prefrontal cortex, an area known to encode the value of options during choices, correlates with the capital gains of potential trades; that the neural measures of realization utility correlate across subjects with their individual tendency to exhibit a disposition effect; and that activity in the ventral striatum, an area known to encode information about changes in the present value of experienced utility, exhibits a positive response when subjects realize capital gains. These results provide support for the realization utility model and, more generally, demonstrate how neural data can be helpful in testing models of investor behavior.