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Monte Carlo Simulation with Asymptotic Method

Author

Listed:
  • Akihiko Takahashi

    (Faculty of Economics and Graduate School of Mathematical Sciences, University of Tokyo)

  • Nakahiro Yoshida

    (Graduate School of Mathematical Sciences, University of Tokyo)

Abstract

We shall propose a new computational scheme with the asymptotic method to achieve variance reduction of Monte Carlo simulation for numerical analysis especially in finance. We not only provide general scheme of our method, but also show its effectiveness through numerical examples such as com-puting optimal portfolio and pricing an average option. Finally, we show mathematical validity of our method.

Suggested Citation

  • Akihiko Takahashi & Nakahiro Yoshida, 2003. "Monte Carlo Simulation with Asymptotic Method," CIRJE F-Series CIRJE-F-249, CIRJE, Faculty of Economics, University of Tokyo.
    • Handle: RePEc:tky:fseres:2003cf249
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    Cited by:

    1. Naoto Kunitomo & Yong-Jin Kim, 2000. "Effects of Stochastic Interest Rates and Volatility on Contingent Claims," CIRJE F-Series CIRJE-F-67, CIRJE, Faculty of Economics, University of Tokyo.
    2. Naoto Kunitomo & Yong-Jin Kim, 2001. "Effects of Stochastic Interest Rates and Volatility on Contingent Claims (Revised Version)," CIRJE F-Series CIRJE-F-129, CIRJE, Faculty of Economics, University of Tokyo.
    3. Naoto Kunitomo & Akihiko Takahashi, 2003. "Applications of the Asymptotic Expansion Approach based on Malliavin-Watanabe Calculus in Financial Problems," CIRJE F-Series CIRJE-F-245, CIRJE, Faculty of Economics, University of Tokyo.
    4. Naoto Kunitomo & Yong‐Jin Kim, 2007. "Effects Of Stochastic Interest Rates And Volatility On Contingent Claims," The Japanese Economic Review, Japanese Economic Association, vol. 58(1), pages 71-106, March.

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