DMCA
The Dynamics of Stochastic Volatility: Evidence from Underlying and Option Markets (2000)
| Citations: | 159 - 3 self |
BibTeX
@MISC{Jones00thedynamics,
author = {Christopher S. Jones},
title = {The Dynamics of Stochastic Volatility: Evidence from Underlying and Option Markets },
year = {2000}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
This paper proposes and estimates a more general parametric stochastic variance model of equity index returns than has been previously considered using data from both underlying and options markets. The parameters of the model under both the objective and riskneutral measures are estimated simultaneously. I conclude that the square root stochastic variance model of Heston (1993) and others is incapable of generating realistic returns behavior and find that the data are more accurately represented by a stochastic variance model in the CEV class or a model that allows the price and variance processes to have a time-varying correlation. Specifically, I find that as the level of market variance increases, the volatility of market variance increases rapidly and the correlation between the price and variance processes becomes substantially more negative. The heightened heteroskedasticity in market variance that results generates realistic crash probabilities and dynamics and causes returns to display values of skewness and kurtosis much more consistent with their sample values. While the model dramatically improves the fit of options prices relative to the square root process, it falls short of explaining the implied volatility smile for short-dated options.
Keyphrases
option market stochastic volatility variance process market variance increase cev class realistic crash probability short-dated option heightened heteroskedasticity square root stochastic variance model stochastic variance model riskneutral measure equity index return realistic return behavior option price sample value market variance implied volatility smile square root process general parametric stochastic variance model time-varying correlation
