The Journal of Finance

Investing for the Long Run when Returns Are Predictable

Published: 03/31/2007   |   DOI: 10.1111/0022-1082.00205

Nicholas Barberis

We examine how the evidence of predictability in asset returns affects optimal portfolio choice for investors with long horizons. Particular attention is paid to estimation risk, or uncertainty about the true values of model parameters. We find that even after incorporating parameter uncertainty, there is enough predictability in returns to make investors allocate substantially more to stocks, the longer their horizon. Moreover, the weak statistical significance of the evidence for predictability makes it important to take estimation risk into account; a long‐horizon investor who ignores it may overallocate to stocks by a sizeable amount.

Mental Accounting, Loss Aversion, and Individual Stock Returns

Published: 12/17/2002   |   DOI: 10.1111/0022-1082.00367

Nicholas Barberis, Ming Huang

We study equilibrium firm‐level stock returns in two economies: one in which investors are loss averse over the fluctuations of their stock portfolio, and another in which they are loss averse over the fluctuations of individual stocks that they own. Both approaches can shed light on empirical phenomena, but we find the second approach to be more successful: In that economy, the typical individual stock return has a high mean and excess volatility, and there is a large value premium in the cross section which can, to some extent, be captured by a commonly used multifactor model.

What Drives the Disposition Effect? An Analysis of a Long‐Standing Preference‐Based Explanation

Published: 03/13/2009   |   DOI: 10.1111/j.1540-6261.2009.01448.x

NICHOLAS BARBERIS, WEI XIONG

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.

Prospect Theory and Stock Market Anomalies

Published: 06/05/2021   |   DOI: 10.1111/jofi.13061

NICHOLAS BARBERIS, LAWRENCE J. JIN, BAOLIAN WANG

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.

Using Neural Data to Test a Theory of Investor Behavior: An Application to Realization Utility

Published: 11/18/2013   |   DOI: 10.1111/jofi.12126

CARY FRYDMAN, NICHOLAS BARBERIS, COLIN CAMERER, PETER BOSSAERTS, ANTONIO RANGEL

We conduct a study in which subjects trade stocks in an experimental market while we measure their brain activity using functional magnetic resonance imaging. All of the subjects trade in a suboptimal way. We use the neural data to test a “realization utility” explanation for their behavior. We find that activity in two areas of the brain that are important for economic decision‐making exhibit activity consistent with the predictions of realization utility. These results provide support for the realization utility model. More generally, they demonstrate that neural data can be helpful in testing models of investor behavior.