Tail Risk and Asset Prices
University of Chicago · Cornell University · +4 more institutions
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 among individual stocks. Our tail measure is significantly correlated with tail risk measures extracted from S&P 500 index options and negatively predicts real economic activity. We show that tail risk has strong predictive power for aggregate market returns. 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. We explore potential mechanisms giving rise to these asset pricing facts.
Citation impact
- FWCI
- 61.15
- Percentile
- 100%
- References
- 91
Authors
2- BKBryan KellyCorresponding
University of Chicago, Cornell University, National Bureau of Economic Research, The University of Texas at Austin, Federal Reserve Board of Governors, Federal Reserve
- HJHao Jiang
The University of Texas at Austin, Cornell University, University of Chicago, National Bureau of Economic Research, Federal Reserve Board of Governors, Federal Reserve
Topics & keywords
- Asset (computer security)
- Economics
- Monetary economics
- Financial economics
- Business
- Computer science