Predicting the equity risk premium using the smooth cross-sectional tail risk: the importance of correlation

• Autor(a) principal: Faias, José Afonso
• Data de Publicação: 2022
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.14/38328
• topic: Equity premium; Prediction; Cross-sectional

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.