Predicting Equity Risk Premium Using the Smooth Cross-Sectional Tail Risk: The Importance of Correlation
45 Pages Posted: 6 Sep 2015 Last revised: 23 Mar 2018
Date Written: July 28, 2017
We provide a new monthly cross-sectional measure of stock market tail risk, defined as the average of the daily cross-sectional tail risk, rather than the tail risk of the pooled daily returns within a month. The former better captures monthly tail risk rather than merely the tail risk on specific days within a month. Using simulations, we attest that this is due to the low value of daily correlations. We show that this difference is important in generating strong in- and out-of-sample predictability and performs better than the historical risk premium and other commonly used predictors for short- and long-term horizons. This strong predictability improves investor performance in a mean-variance setting.
Keywords: Equity Premium, Prediction, Cross-sectional
JEL Classification: G11, G14, G17
Suggested Citation: Suggested Citation