Jump and volatility dynamics for the s&p500: evidence for infinite-activity jumps with non-affine volatility dynamics from stock and option markets
Research output: Contribution to journal › Article › Scientific › peer-review
|Journal||REVIEW OF FINANCE|
|Early online date||2016|
|Publication status||Published - Mar 2017|
|Publication type||A1 Journal article-refereed|
Relatively little is known about the empirical performance of infinite-activity Levy jump models, especially with non-affine volatility dynamics. We use extensive empirical data sets to study how infinite-activity Variance Gamma and Normal Inverse Gaussian jumps with affine and non-affine volatility dynamics improve goodness of fit and option pricing performance. With Markov Chain Monte Carlo, different model specifications are estimated using the joint information of the S&P 500 index and the VIX. Our paper provides clear evidence that a parsimonious non-affine model with Normal Inverse Gaussian return jumps and a linear variance specification is particularly competitive, even during the recent crisis.