Predicting equity risk premium using smooth cross-sectional tail risk

2018-03-16 14:43:53

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 by José Faias

WHEN: Thursday, August 31, 12 p.m. – 1 p.m.

WHERE: Block C3 (GSB/GSPP Building), 3rd floor, Room 3038

ABSTRACT: 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. 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. 

SPEAKER: José Faias

Assistant Professor

Visiting Fellow

Católica Lisbon School of Business & Economics

Universidade Católica Portuguesa

Lisboa, Portugal

José Faias holds a PhD in Finance (FE-UNL), a MSc in Statistics and Optimization (FCT-UNL), an MBA (CATÓLICA-LISBON) and a BA (“Licenciatura”) in Mathematics – Actuarial Sciences (FCT-UNL). He was a visiting fellow at Harvard University. He has previously taught at FE-UNL and worked in the insurance and investment banking industry. His research interests include empirical asset pricing and econometrics: option pricing, extreme events, regime switching models, international financial markets, risk management, and quantitative portfolio management.