Volatility Skew, Earnings Announcements, and the Predictability of Crashes
Andrew Van Buskirk
Ohio State University (OSU) - Department of Accounting & Management Information Systems
April 28, 2011
This paper examines the relation between firm-level implied volatility skew and the likelihood of extreme negative events, or crash risk. I show that volatility skew identifies which firms are likely to experience crashes, but only in short-window earnings announcement periods. The predictive power is incremental to the information in historical volatility, financial reporting opacity, and even the current period’s earnings surprise. In contrast, volatility skew does not predict crashes outside of earnings periods, even in regressions with few independent variables, and even when those periods include management earnings forecasts. At best, volatility skew contains modest information about future price declines, but only when looking at cumulative returns over several months. While prior research concludes that volatility skew contains information about future earnings shocks, these results indicate that, outside of quarterly earnings announcements, option investors have difficulty predicting when the adverse earnings news will be revealed.
Number of Pages in PDF File: 55
Keywords: Implied Volatility, Earnings Announcement, Options
JEL Classification: G13, G14, M41working papers series
Date posted: January 15, 2011 ; Last revised: May 4, 2011
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