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Applications of Malliavin calculus to Monte-Carlo methods in finance. II

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  • Eric Fournié

    (PARIBAS Capital Markets, 10, Harewood Avenue, NW1 6AA London, England)

  • Jean-Michel Lasry

    (PARIBAS Capital Markets, 10, Harewood Avenue, NW1 6AA London, England)

  • Pierre-Louis Lions

    ()
    (Ceremade, UMR 9534, Université Paris-Dauphine, Place Maréchal de Lattre de Tassigny, 75775 Paris Cedex 16, France)

  • Jérôme Lebuchoux

    (PARIBAS Capital Markets, 10, Harewood Avenue, NW1 6AA London, England)

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    Abstract

    This paper is the sequel of Part I [1], where we showed how to use the so-called Malliavin calculus in order to devise efficient Monte-Carlo (numerical) methods for Finance. First, we return to the formulas developed in [1] concerning the "greeks" used in European options, and we answer to the question of optimal weight functional in the sense of minimal variance. Then, we investigate the use of Malliavin calculus to compute conditional expectations. The integration by part formula provides a powerful tool when used in the framework of Monte Carlo simulation. It allows to compute everywhere, on a single set of trajectories starting at one point, solution of general options related PDEs. Our final application of Malliavin calculus concerns the use of Girsanov transforms involving anticipating drifts. We give an example in numerical Finance of such a transform which gives reduction of variance via importance sampling. Finally, we include two appendices that are concerned with the PDE interpretation of the formulas presented in [1] for the delta of a European option and with the connections between the functional dependence of some random variables and their Malliavin derivatives.

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    Bibliographic Info

    Article provided by Springer in its journal Finance and Stochastics.

    Volume (Year): 5 (2001)
    Issue (Month): 2 ()
    Pages: 201-236

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    Handle: RePEc:spr:finsto:v:5:y:2001:i:2:p:201-236

    Note: received: February 1999; final version received: January 2000
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    Related research

    Keywords: Monte Carlo methods; Malliavin calculus; hedge ratios and greeks; conditional expectations; PDE; anticipative Girsanov transform; functional dependence;

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    Cited by:
    1. Arturo Kohatsu-Higa & Miquel Montero, 2001. "An application of Malliavin Calculus to Finance," Papers cond-mat/0111563, arXiv.org.
    2. Akihiko Takahashi & Toshihiro Yamada, 2009. "An Asymptotic Expansion with Malliavin Weights: An Application to Pricing Discrete Barrier Options," CIRJE F-Series CIRJE-F-696, CIRJE, Faculty of Economics, University of Tokyo.
    3. Fard, Farzad Alavi & Siu, Tak Kuen, 2013. "Pricing participating products with Markov-modulated jump–diffusion process: An efficient numerical PIDE approach," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 712-721.
    4. Fujiwara, Hajime & Kijima, Masaaki, 2007. "Pricing of path-dependent American options by Monte Carlo simulation," Journal of Economic Dynamics and Control, Elsevier, vol. 31(11), pages 3478-3502, November.
    5. Akihiko Takahashi & Toshihiro Yamada, 2012. "A Remark on Approximation of the Solutions to Partial Differential Equations in Finance," CIRJE F-Series CIRJE-F-842, CIRJE, Faculty of Economics, University of Tokyo.
    6. Akihiko Takahashi & Toshihiro Yamada, 2009. "An Asymptotic Expansion with Malliavin Weights: An Application to Pricing Discrete Barrier Options," CARF F-Series CARF-F-193, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    7. N. Hilber & N. Reich & C. Schwab & C. Winter, 2009. "Numerical methods for Lévy processes," Finance and Stochastics, Springer, vol. 13(4), pages 471-500, September.
    8. Boyle, Phelim & Imai, Junichi & Tan, Ken Seng, 2008. "Computation of optimal portfolios using simulation-based dimension reduction," Insurance: Mathematics and Economics, Elsevier, vol. 43(3), pages 327-338, December.
    9. Moez Mrad & Nizar Touzi & Amina Zeghal, 2006. "Monte Carlo Estimation of a Joint Density Using Malliavin Calculus, and Application to American Options," Computational Economics, Society for Computational Economics, vol. 27(4), pages 497-531, June.
    10. Detemple, Jerome & Rindisbacher, Marcel, 2007. "Monte Carlo methods for derivatives of options with discontinuous payoffs," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3393-3417, April.
    11. Boyle, Phelim & Potapchik, Alexander, 2008. "Prices and sensitivities of Asian options: A survey," Insurance: Mathematics and Economics, Elsevier, vol. 42(1), pages 189-211, February.
    12. Farzad Fard & Ning Rong, 2014. "Pricing and managing risks of ruin contingent life annuities under regime switching variance gamma process," Annals of Finance, Springer, vol. 10(2), pages 315-332, May.
    13. Tebaldi, Claudio, 2005. "Hedging using simulation: a least squares approach," Journal of Economic Dynamics and Control, Elsevier, vol. 29(8), pages 1287-1312, August.
    14. Bouchard, Bruno & Touzi, Nizar, 2004. "Discrete-time approximation and Monte-Carlo simulation of backward stochastic differential equations," Stochastic Processes and their Applications, Elsevier, vol. 111(2), pages 175-206, June.
    15. Chen, Nan & Glasserman, Paul, 2007. "Malliavin Greeks without Malliavin calculus," Stochastic Processes and their Applications, Elsevier, vol. 117(11), pages 1689-1723, November.
    16. Akihiko Takahashi & Toshihiro Yamada, 2012. "A Remark on Approximation of the Solutions to Partial Differential Equations in Finance," CARF F-Series CARF-F-273, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo, revised Mar 2012.

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