Pricing VIX derivatives with infinite-activity jumps

Jiling Cao, Xinfeng Ruan, Shu Su, Wenjun Zhang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)329-354
Number of pages26
JournalJournal of Futures Markets
Issue number3
Publication statusPublished - 1 Mar 2020
Externally publishedYes


  • VIX derivatives
  • infinite-activity jumps
  • maximum log-likelihood estimation
  • unscented Kalman filter


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