Forecasting Crashes with a Smile
Participer
Département: Finance
Intervenant: Ian Martin (LSE)
Salle: TBD
Forecasting Crashes with a Smile
Ian W. R. Martin Ran Shi∗ May, 2024
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.