New Testing Approaches for Mean-Variance Predictability
94 Pages Posted: 11 Jan 2019
Date Written: January 2019
Abstract
We propose tests for smooth but persistent serial correlation in risk premia and volatilities that exploit the non-normality of financial returns. Our parametric tests are robust to distributional misspecification, while our semiparametric tests are as powerful as if we knew the true return distribution. Local power analyses confirm their gains over existing methods, while Monte Carlo exercises assess their finite sample reliability. We apply our tests to quarterly returns on the five Fama-French factors for international stocks, whose distributions are mostly symmetric and fat-tailed. Our results highlight noticeable differences across regions and factors and confirm the fragility of Gaussian tests.
Keywords: Financial forecasting, Misspecification, Moment tests, robustness, volatility
JEL Classification: C12, C22, G17
Suggested Citation: Suggested Citation