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Sensitivity Analysis And Density Estimation For The Hobson-Rogers Stochastic Volatility Model

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  • REIICHIRO KAWAI

    ()
    (Center for the Study of Finance and Insurance, Osaka University, Toyonaka, 560-8531, Japan)

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    Abstract

    Monte Carlo estimators of sensitivity indices and the marginal density of the price dynamics are derived for the Hobson-Rogers stochastic volatility model. Our approach is based mainly upon the Kolmogorov backward equation by making full use of the Markovian property of the dynamics given the past information. Some numerical examples are presented with a GARCH-like volatility function and its extension to illustrate the effectiveness of our formulae together with a clear exhibition of the skewness and the heavy tails of the price dynamics.

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    Bibliographic Info

    Article provided by World Scientific Publishing Co. Pte. Ltd. in its journal International Journal of Theoretical and Applied Finance.

    Volume (Year): 12 (2009)
    Issue (Month): 03 ()
    Pages: 283-295

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    Handle: RePEc:wsi:ijtafx:v:12:y:2009:i:03:p:283-295

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    Related research

    Keywords: Asset price dynamics; density estimation; GARCH; Kolmogorov backward equation; Markov processes; Monte Carlo simulation; sensitivity analysis; stochastic volatility;

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    Cited by:
    1. Mauro Rosestolato & Tiziano Vargiolu & Giovanna Villani, 2013. "Robustness for path-dependent volatility models," Decisions in Economics and Finance, Springer, vol. 36(2), pages 137-167, November.

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