Tail Risk and Asset Prices

55 Pages Posted: 5 Sep 2013 Last revised: 11 Jan 2014

Bryan T. Kelly

University of Chicago - Booth School of Business; National Bureau of Economic Research (NBER)

Hao Jiang

Erasmus University Rotterdam (EUR)

Multiple version iconThere are 2 versions of this paper

Date Written: August 1, 2013

Abstract

We propose a new measure of time-varying tail risk that is directly estimable from the cross section of returns. We exploit firm-level price crashes every month to identify common fluctuations in tail risk across stocks. Our tail measure is significantly correlated with tail risk measures extracted from S&P 500 index options, but is available for a longer sample since it is calculated from equity data. We show that tail risk has strong predictive power for aggregate market returns: A one standard deviation increase in tail risk forecasts an increase in excess market returns of 4.5% over the following year. Cross-sectionally, stocks with high loadings on past tail risk earn an annual three-factor alpha 5.4% higher than stocks with low tail risk loadings. These findings are consistent with asset pricing theories that relate equity risk premia to rare disasters or other forms of tail risk.

Keywords: tail risk, time-varying risk, conditional expected returns, cross section of returns

JEL Classification: G11, G12, G13, G17

Suggested Citation

Kelly, Bryan T. and Jiang, Hao, Tail Risk and Asset Prices (August 1, 2013). Chicago Booth Research Paper No. 13-67. Available at SSRN: https://ssrn.com/abstract=2321243 or http://dx.doi.org/10.2139/ssrn.2321243

Bryan T. Kelly (Contact Author)

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States
773-702-8359 (Phone)

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Hao Jiang

Erasmus University Rotterdam (EUR) ( email )

Burgemeester Oudlaan 50
3000 DR Rotterdam, Zuid-Holland 3062PA
Netherlands

Paper statistics

Downloads
1,420
Rank
9,126
Abstract Views
6,163