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Review of Derivatives Research

, Volume 22, Issue 1, pp 41–75 | Cite as

Pricing VIX derivatives with free stochastic volatility model

  • Wei LinEmail author
  • Shenghong Li
  • Shane Chern
  • Jin E. Zhang
Article
  • 137 Downloads

Abstract

This paper aims to develop a new free stochastic volatility model, joint with jumps. By freeing the power parameter of instantaneous variance, this paper takes Heston model and 3/2 model for special examples, and extends the generalizability. This model is named after free stochastic volatility model, and it owns two distinctive features. First of all, the power parameter is not constrained, so as to enable the data to voice its authentic direction. The Generalized Methods of Moments suggest that the purpose of this newly-added parameter is to create various volatility fluctuations observed in financial market. Secondly, even upward and downward jumps are separately modeled to accommodate the market data, this paper still provides the quasi-closed-form solutions for futures and option prices. Consequently, the model is novel and highly tractable. Here, it should be noted that the data on VIX futures and corresponding option contracts is employed to evaluate the model, in terms of its pricing and implied volatility features capturing performance. To sum up, the free stochastic volatility model with asymmetric jumps is capable of adequately capturing the implied volatility dynamics. Thus, it can be regarded as a model advantageous in pricing VIX derivatives with fixed power volatility models.

Keywords

Free stochastic volatility Jumps VIX derivatives 

JEL Classification

G13 

Notes

Acknowledgements

This work is supported by the National Natural Science Foundation of China (No. 11571310A011402) and Jin E. Zhang has been supported by an establishment grant from the University of Otago and the National Natural Science Foundation of China (Project No. 71771199).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Mathematical SciencesZhejiang UniversityHangzhouChina
  2. 2.Pennsylvania State UniversityState CollegeUSA
  3. 3.Department of Accountancy and FinanceUniversity of OtagoDunedinNew Zealand

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