On the Economic Significance of Stock Return Predictability
80 Pages Posted: 10 May 2019 Last revised: 30 Dec 2019
Date Written: December 29, 2019
Kandel and Stambaugh (1996) demonstrate that forecasting variables with weak statistical support in predictive return regressions can exert considerable economic influence on portfolio decisions. Using a Bayesian vector autoregression framework with stochastic volatility in market returns and predictor variables, we assess the economic value of return predictability for investors and reach a complementary conclusion. Statistically strong predictors can be economically unimportant if they tend to take extreme values in high-volatility periods, have low persistence, or follow distributions with fat tails. Several popular predictors exhibit these properties such that their impressive statistical results do not translate into large economic gains.
Keywords: Market return predictability, Bayesian investors, Stochastic volatility, Multiperiod horizons
JEL Classification: G10, G11, G12
Suggested Citation: Suggested Citation