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Pricing VIX derivatives with infinite-activity jumps
Authors:Jiling Cao  Xinfeng Ruan  Shu Su  Wenjun Zhang
Affiliation:1. Department of Mathematical Sciences, School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand;2. Department of Accountancy and Finance, Otago Business School, University of Otago, Dunedin, New Zealand
Abstract: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), J Financ Econ, 108, 367–391. 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  maximum log-likelihood estimation  unscented Kalman filter  VIX derivatives
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