Journal of Financial Markets Vol. 63 2023
Predicting the equity risk premium using the smooth cross-sectional tail risk: The importance of correlation
open access
Abstract
I provide a new monthly cross-sectional measure of stock market tail risk, SCSTR, defined as the average of the daily cross-sectional tail risk, rather than the tail risk of the pooled daily returns within a month. Through simulations, I find that SCSTR better captures monthly tail risk rather than merely the tail risk on specific days within a month. In an extended period from 1964 until 2018, 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.
- DOI
- 10.1016/j.finmar.2022.100769
- Volume
- 63
- Pages
- 100769
- Language
- en
- Sources
- crossref openalex