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Sample Path Generation of the Stochastic Volatility CGMY Process and Its Application to Path-Dependent Option Pricing

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  • Young Shin Kim

    (College of Business, Stony Brook University, Stony Brook, NY 11794, USA)

Abstract

This paper proposes the sample path generation method for the stochastic volatility version of the CGMY process. We present the Monte-Carlo method for European and American option pricing with the sample path generation and calibrate model parameters to the American style S&P 100 index options market, using the least square regression method. Moreover, we discuss path-dependent options, such as Asian and Barrier options.

Suggested Citation

  • Young Shin Kim, 2021. "Sample Path Generation of the Stochastic Volatility CGMY Process and Its Application to Path-Dependent Option Pricing," JRFM, MDPI, vol. 14(2), pages 1-18, February.
    • Handle: RePEc:gam:jjrfmx:v:14:y:2021:i:2:p:77-:d:499509
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    References listed on IDEAS

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    Cited by:

    1. Søren Asmussen, 2022. "On the role of skewness and kurtosis in tempered stable (CGMY) Lévy models in finance," Finance and Stochastics, Springer, vol. 26(3), pages 383-416, July.

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