Pricing VIX Derivatives with Infinite-Activity Jumps
46 Pages Posted: 11 Nov 2019
Date Written: October 30, 2019
In this paper, we investigate a two-factor VIX model with infinite-activity jumps, which is a more realistic way to reduce errors in pricing VIX derivatives, compared with Mencía and Sentana (2013). Our two-factor model features central tendency, stochastic volatility and infinite-activity pure jump Lévy processes which include the variance gamma (VG) and the normal inverse Gaussian (NIG) processes as special cases. We find empirical evidence that the model with infinite-activity jumps is superior to the models with finite-activity jumps, particularly in pricing VIX options. As a result, infinite-activity jumps should not be ignored in pricing VIX derivatives.
Keywords: Infinite-activity jumps, VIX derivatives, unscented Kalman filter, maximum log-likelihood estimation
JEL Classification: G12, G13
Suggested Citation: Suggested Citation