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Forecasting crashes with a smile

Author

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  • Martin, Ian
  • Shi, Ran

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.

Suggested Citation

  • Martin, Ian & Shi, Ran, 2023. "Forecasting crashes with a smile," CEPR Discussion Papers 18524, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:18524
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    More about this item

    Keywords

    forecasts;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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