Forecasting Crashes with a Smile

Department: Finance

Speaker: Ian Martin (LSE)

Room: TBD

Abstract

We use option prices to derive bounds on the probability of a crash in an individual stock, and argue that the lower bound should be close to the truth. Empirically, the lower bound is highly statistically and economically significant; on its own, it outperforms 15 stock characteristics proposed by the prior literature combined. In a multivariate regression, a one standard deviation increase in the bound raises the predicted crash probability by 3 percentage points, whereas a one standard deviation increase in the next most important predictor (a measure of short interest) raises the predicted probability by only 0.3 percentage points.