Why do value stocks have higher average returns than growth stocks, despite having lower risk? Why do these stocks exhibit positive abnormal performance, while growth stocks exhibit negative abnormal performance? This paper offers a rare-event-based explanation that can also account for the high equity premium and volatility of the aggregate market. The model explains other puzzling aspects of the data, such as joint patterns in time-series predictablity of aggregate market and value and growth returns, long periods in which growth outperforms value, and the association between positive skewness and low realized returns.

[We develop a life-cycle consumption and portfolio choice model in which households have nonhomothetic utility over two types of goods, basic and luxury. We calibrate the model to match the cross-sectional and life-cycle variation in the basic expenditure share in the Consumer Expenditure Survey. The model explains the degree to which the portfolio share in risky assets rises in wealth in the cross-section of households in the Survey of Consumer Finances. For a given household, the portfolio share can fall in response to an increase in wealth, even though the model implies decreasing relative risk aversion.]

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

Sovereign debt yields have undergone a historic decline over the last half century. Standard explanations, including aging populations and increases in asset demand from abroad, encounter difficulties when confronted with the full range of evidence. We propose an explanation based on a decline in inflation and default risk. We show that a model with sovereign default captures the decline in interest rates, the stability of equity valuation ratios, and the reduction in investment and output growth. Calibrations of the model post-COVID suggest that sovereign default risk may have returned.

[Aggregate stock prices, relative to virtually any indicator of fundamental value, soared to unprecedented levels in the 1990s. Even today, after the market declines since 2000, they remain well above historical norms. Why? We consider one particular explanation: A fall in macroeconomic risk, or the volatility of the aggregate economy. Empirically, we find a strong correlation between low-frequency movements in macroeconomic volatility and low-frequency movements in the stock market. To model this phenomenon, we estimate a two-state regime switching model for the volatility and mean of consumption growth, and find evidence of a shift to substantially lower consumption volatility at the beginning of the 1990s. We then use these estimates from postwar data to calibrate a rational asset pricing model with regime switches in both the mean and standard deviation of consumption growth. Plausible parameterizations of the model are found to account for a significant portion of the run-up in asset valuation ratios observed in the late 1990s.]

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.