A Closed Form Solution for Pricing Variance Swaps Under the Rescaled Double Heston Model

Youngin Yoon, Jeong Hoon Kim

Research output: Contribution to journalArticlepeer-review

Abstract

As is well known, multi-factor stochastic volatility models are necessary to capture the market accurately in pricing financial derivatives. However, the multi-factor models usually require too many parameters to be calibrated efficiently and they do not lead to an analytic pricing formula. The double Heston model is one of them. The approach of this paper for this difficulty is to rescale the double Heston model to reduce the number of the model parameters and obtain a closed form analytic solution formula for variance swaps explicitly. We show that the rescaled double Heston model is as effective as the original double Heston model in terms of fitting to the VIX market data in a stable condition and yet the computing time is much less than that under the double Heston model. However, in a turbulent situation after the start of the COVID-19 pandemic in 2020, we acknowledge that even the double Heston model fails to capture the market accurately.

Original languageEnglish
JournalComputational Economics
DOIs
Publication statusAccepted/In press - 2021

Bibliographical note

Funding Information:
We thank the anonymous referees for their careful reading of our earlier version of the manuscript and their insightful comments and suggestions. The research of J.-H. Kim was supported by the National Research Foundation of Korea NRF2021R1A2C1004080.

Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

All Science Journal Classification (ASJC) codes

  • Economics, Econometrics and Finance (miscellaneous)
  • Computer Science Applications

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