Pricing VIX Derivatives with Infinite-Activity Jumps

Journal of Futures Markets

46 Pages Posted: 11 Nov 2019 Last revised: 3 Aug 2021

See all articles by Jiling Cao

Jiling Cao

Auckland University of Technology

Xinfeng Ruan

Xi'an Jiaotong-Liverpool University

Shu Su

Auckland University of Technology

wenjun zhang

Auckland University of Technology

Date Written: October 30, 2019

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). 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

Cao, Jiling and Ruan, Xinfeng and Su, Shu and zhang, wenjun, Pricing VIX Derivatives with Infinite-Activity Jumps (October 30, 2019). Journal of Futures Markets, Available at SSRN: https://ssrn.com/abstract=3478340 or http://dx.doi.org/10.2139/ssrn.3478340

Jiling Cao

Auckland University of Technology ( email )

AUT City Campus
Private Bag 92006
Auckland, 1142
New Zealand

Xinfeng Ruan

Xi'an Jiaotong-Liverpool University ( email )

111 Renai Road, SIP
Suzhou, JiangSu province 215123
China

Shu Su

Auckland University of Technology ( email )

AUT City Campus
Private Bag 92006
Auckland, 1142
New Zealand

Wenjun Zhang (Contact Author)

Auckland University of Technology ( email )

AUT City Campus
Private Bag 92006
Auckland, 1142
New Zealand

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
76
Abstract Views
696
Rank
554,144
PlumX Metrics