Sequential Itô–Taylor expansions and characteristic functions of stochastic volatility models

Kailin Ding, Zhenyu Cui, Yanchu Liu

Research output: Contribution to journalArticlepeer-review

Abstract

This study proposes a new approach to derive the characteristic function of a general stochastic volatility model by sequentially utilizing the Itô–Taylor expansions. In particular, our method applies to non-affine stochastic volatility models with jumps, for which the corresponding characteristic functions do not have closed-form expressions. Numerically inverting these characteristic functions can yield accurate probability density functions of stochastic volatility models to serve for various pricing and hedging purposes in quantitative finance. The proposed sequential Itô–Taylor expansion allows us to handle derivatives with medium to long maturities. Numerical experiments illustrate the accuracy and effectiveness of our approach.

Original languageEnglish
Pages (from-to)1750-1769
Number of pages20
JournalJournal of Futures Markets
Volume43
Issue number12
DOIs
StatePublished - Dec 2023

Keywords

  • Itô–Taylor expansion
  • characteristic functions
  • derivatives pricing
  • stochastic volatility

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