The Journal of Finance

Asset‐pricing Tests under Alternative Distributions

Published: 12/01/1993   |   DOI: 10.1111/j.1540-6261.1993.tb05134.x

GUOFU ZHOU

Given the normality assumption, we reject the mean‐variance efficiency of the Center for Research in Security Prices value‐weighted stock index for three of the six consecutive ten‐year subperiods from 1926 to 1986. However, the normality assumption is strongly rejected by the data. Under plausible alternative distributional assumptions of the elliptical class, the efficiency can no longer be rejected. When the normality assumption is violated but the ellipticity assumption is maintained, many tests tend to be biased toward overrejection and both the accuracy of estimated beta and R2 are usually overstated.

A Critique of the Stochastic Discount Factor Methodology

Published: 12/17/2002   |   DOI: 10.1111/0022-1082.00145

Raymond Kan, Guofu Zhou

In this paper, we point out that the widely used stochastic discount factor (SDF) methodology ignores a fully specified model for asset returns. As a result, it suffers from two potential problems when asset returns follow a linear factor model. The first problem is that the risk premium estimate from the SDF methodology is unreliable. The second problem is that the specification test under the SDF methodology has very low power in detecting misspecified models. Traditional methodologies typically incorporate a fully specified model for asset returns, and they can perform substantially better than the SDF methodology.

International Stock Return Predictability: What Is the Role of the United States?

Published: 03/19/2013   |   DOI: 10.1111/jofi.12041

DAVID E. RAPACH, JACK K. STRAUSS, GUOFU ZHOU

We investigate lead‐lag relationships among monthly country stock returns and identify a leading role for the United States: lagged U.S. returns significantly predict returns in numerous non‐U.S. industrialized countries, while lagged non‐U.S. returns display limited predictive ability with respect to U.S. returns. We estimate a news‐diffusion model, and the results indicate that return shocks arising in the United States are only fully reflected in equity prices outside of the United States with a lag, consistent with a gradual information diffusion explanation of the predictive power of lagged U.S. returns.

Anomalies and the Expected Market Return

Published: 12/06/2021   |   DOI: 10.1111/jofi.13099

XI DONG, YAN LI, DAVID E. RAPACH, GUOFU ZHOU

We provide the first systematic evidence on the link between long‐short anomaly portfolio returns—a cornerstone of the cross‐sectional literature—and the time‐series predictability of the aggregate market excess return. Using 100 representative anomalies from the literature, we employ a variety of shrinkage techniques (including machine learning, forecast combination, and dimension reduction) to efficiently extract predictive signals in a high‐dimensional setting. We find that long‐short anomaly portfolio returns evince statistically and economically significant out‐of‐sample predictive ability for the market excess return. The predictive ability of anomaly portfolio returns appears to stem from asymmetric limits of arbitrage and overpricing correction persistence.