Measuring Tail Risks at High Frequency

I exploit information in the cross-section of bid-ask spreads to develop a new measure of extreme event risk. Spreads embed tail risk information because liquidity providers require compensation for the possibility of sharp changes in asset values. I show that simple regressions relating spreads and trading volume to factor betas recover this information and deliver high-frequency tail risk estimates for common factors in stock returns. My methodology disentangles financial and aggregate market risks during the 2007–2008 financial crisis; quantifies jump risks associated with Federal Open Market Committee announcements; and anticipates an extreme liquidity shock before the 2010 Flash Crash. Received April 27, 2016; editorial decision August 10, 2018 by Editor Andrew Karolyi. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online