Working Paper: NBER ID: w19375
Authors: Bryan Kelly; Hao Jiang
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; asset prices; market returns
JEL Codes: G01; G12; G13; G17
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| tail risk (D81) | excess market returns (G12) |
| tail risk (D81) | required returns by investors (G12) |
| tail risk (D81) | market dynamics (D49) |
| tail risk (D81) | three-factor alpha (C38) |
| tail risk (D81) | returns (Y60) |
| tail risk (D81) | equity risk premia (G12) |