Jumps and Diffusive Variance: A Granular Analysis of Individual Stock Returns
46 Pages Posted: 26 Apr 2021 Last revised: 4 Jun 2021
Date Written: April 25, 2021
Jumps and diffusive changes in stock prices are different ways in which information is reflected in the prices. We use nonparametric methods to decompose returns on individual stocks into jumps and diffusive components. Contrary to the conventional assumption that jump intensity is positively related to diffusive variance, we find abundant evidence that realized jump intensity and diffusive variance are uncorrelated or negatively related for a majority of stocks. The jump-diffusion beta is found to positively contribute to the implied volatility smile of options on individual stocks. We also document a counter-cyclical pattern of realized jump sizes, which challenges the i.i.d. jump size assumption commonly seen in the literature. The findings provide useful guidance on modeling option prices.
Keywords: Jumps, Diffusive Variance, Implied Volatility Smile
JEL Classification: G12
Suggested Citation: Suggested Citation