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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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    2. Kim, Young Shin & Rachev, Svetlozar T. & Bianchi, Michele Leonardo & Mitov, Ivan & Fabozzi, Frank J., 2011. "Time series analysis for financial market meltdowns," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1879-1891, August.
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    6. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," University of California at Los Angeles, Anderson Graduate School of Management qt43n1k4jb, Anderson Graduate School of Management, UCLA.
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    11. Tobias Nigbur, 2011. "Svetlozar T. Rachev, Young Shin Kim, Michele L. Bianchi, Frank J. Fabozzi: Financial models with Lévy processes and volatility clustering," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 25(4), pages 477-478, December.
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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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