Forecasting crashes with a smile

Ian Martin and Ran Shi

No 18524, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: We introduce a framework that uses option prices to deliver upper and lower bounds on the probability of crash in an individual stock, and argue based on a priori considerations that the lower bound should be close to the true crash probability. Empirical tests support this prediction in and out of sample. We horse-race the lower bound against a range of characteristics proposed by the prior literature. The lower bound is highly statistically significant, with a t-statistic above five, and is an order of magnitude more economically significant than any of the characteristics, in the sense that a one standard deviation increase in the lower bound raises the predicted probability of a crash by 3 percentage points, whereas a one standard deviation change in the next most important predictor (a measure of short interest) moves the predicted probability of a crash by only 0.3 percentage points.

Keywords: forecasts (search for similar items in EconPapers)
JEL-codes: G12 G17 (search for similar items in EconPapers)
Date: 2023-10
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