What distribution best characterizes the time series and cross-section of individual stock returns? To answer this question, we estimate the degree of cross-sectional return skewness relative to a benchmark that nests many models considered in the literature. We find that cross-sectional skewness in monthly returns far exceeds what this benchmark model predicts. However, cross-sectional skewness in long-run returns in the data is substantially below what the model predicts. We show that fat-tailed idiosyncratic events appear to be necessary to explain skewness in the data. (JEL, G10, G11, G12, G13, G14).

Jessica A. Wachter, Portfolio and Consumption Decisions under Mean-Reverting Returns: An Exact Solution for Complete Markets, The Journal of Financial and Quantitative Analysis, Vol. 37, No. 1 (Mar., 2002), pp. 63-91

Why is the equity premium so high, and why are stocks so volatile? Why are stock returns in excess of government bill rates predictable? This paper proposes an answer to these questions based on a time‐varying probability of a consumption disaster. In the model, aggregate consumption follows a normal distribution with low volatility most of the time, but with some probability of a consumption realization far out in the left tail. The possibility of this poor outcome substantially increases the equity premium, while time‐variation in the probability of this outcome drives high stock market volatility and excess return predictability.

We reconsider the excess volatility puzzle through the lens of a model in which agents believe they can predict dividend growth when in fact they cannot. Besides excess volatility in the time series, the model explains the value premium, and the explanatory power of the value factor. In support of the model, we show that analysts’ earnings forecasts align with market valuation and that analysts are far more optimistic about growth stocks than they are about value stocks. Using both survey and price data, we show that the same mechanism can explain the excess returns earned by investing in high-interest rate currencies.

The equity premium — the expected return on the aggregate stock market less the government bill rate – is of central importance to the portfolio allocation of individuals, to the investment decisions of firms, and to model calibration and testing. This quantity is usually estimated from the sample average excess return. We propose an alternative estimator, based on maximum likelihood, that takes into account information contained in dividends and prices. Applied to the postwar sample, our method leads to an economically significant reduction from 6.4% to 5.1%. Simulation results show that our method produces more reliable estimates under a wide range of specifications.

What is the driving force behind the cyclical behavior of unemployment and vacancies? What is the relation between firms’ job-creation incentives and stock market valuations? We answer these questions in a model with time-varying risk, modeled as a small and variable probability of an economic disaster. A high probability implies greater risk and lower future growth, lowering the incentives of firms to invest in hiring. During periods of high risk, stock market valuations are low and unemployment rises. The model thus explains volatility in equity and labor markets, and the relation between the two. Received May 12, 2016; editorial decision October 26, 2017 by Editor Stijn Van Nieuwerburgh. Authors have furnished data, which are available on the Oxford University Press Web site next to the link to the final published paper online.

Empirical studies demonstrate striking patterns in stock returns related to scheduled macroeconomic announcements. A large proportion of the total equity premium is realized on days with macroeconomic announcements. The relation between market betas and expected returns is far stronger on announcement days as compared with nonannouncement days. Finally, these results hold for fixed-income investments as well as for stocks. We present a model in which agents learn the probability of an adverse economic state on announcement days. We show that the model quantitatively accounts for the empirical findings. Evidence from options data provides support for the model’s mechanism.

In the cross-section of U.S. households, the portfolio share in risky assets rises in wealth. The standard life-cycle model with power utility and non-tradable labor income has the counterfactual implication that the portfolio share declines in wealth. We develop a life-cycle model in which household utility depends on two types of consumption goods, basic and luxury. The model predicts that the expenditure share for basic goods declines in total consumption, and the variance of consumption growth rises in the level of consumption. When calibrated to match these two predictions in household consumption data, the model explains portfolio shares that rise in wealth.

Studies of human memory indicate that features of an event evoke memories of prior associated contextual states, which in turn become associated with the current event’s features. This retrieved-context mechanism allows the remote past to influence the present, even as agents gradually update their beliefs about their environment. We apply a version of retrieved-context theory, drawn from the literature on human memory, to explain three types of evidence in the financial economics literature: the role of early life experience in shaping investment choices, occurrence of financial crises, and the effect of fear on asset allocation. These applications suggest a recasting of neoclassical rational expectations in terms of beliefs as governed by principles of human memory.