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Monte Carlo Evaluation of Greeks for Multidimensional Barrier and Lookback Options

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  • Guillaume Bernis
  • Emmanuel Gobet
  • Arturo Kohatsu‐Higa

Abstract

In this paper, we consider the problem of the numerical computation of Greeks for a multidimensional barrier and lookback style options: the payoff function depends in a rather general way on the minima and maxima of the coordinates of the d‐dimensional underlying asset process. Using Malliavin calculus techniques, we derive additional weights that enable computation of the Greeks using Monte Carlo simulations. Numerical experiments confirm the efficiency of the method. This work is a multidimensional extension of previous results (see Gobet and Kohatsu‐Higa 2001).

Suggested Citation

  • Guillaume Bernis & Emmanuel Gobet & Arturo Kohatsu‐Higa, 2003. "Monte Carlo Evaluation of Greeks for Multidimensional Barrier and Lookback Options," Mathematical Finance, Wiley Blackwell, vol. 13(1), pages 99-113, January.
    • Handle: RePEc:bla:mathfi:v:13:y:2003:i:1:p:99-113
    DOI: 10.1111/1467-9965.00008
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    References listed on IDEAS

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    1. Mark Broadie & Paul Glasserman, 1996. "Estimating Security Price Derivatives Using Simulation," Management Science, INFORMS, vol. 42(2), pages 269-285, February.
    2. Hans-Peter Bermin, 2000. "Hedging lookback and partial lookback options using Malliavin calculus," Applied Mathematical Finance, Taylor & Francis Journals, vol. 7(2), pages 75-100.
    3. Paul Glasserman & David D. Yao, 1992. "Some Guidelines and Guarantees for Common Random Numbers," Management Science, INFORMS, vol. 38(6), pages 884-908, June.
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    Cited by:

    1. L. Jeff Hong & Sandeep Juneja & Jun Luo, 2014. "Estimating Sensitivities of Portfolio Credit Risk Using Monte Carlo," INFORMS Journal on Computing, INFORMS, vol. 26(4), pages 848-865, November.
    2. Nakatsu, Tomonori, 2023. "On density functions related to discrete time maximum of some one-dimensional diffusion processes," Applied Mathematics and Computation, Elsevier, vol. 441(C).
    3. Kiseop Lee & Seongje Lim & Hyungbin Park, 2022. "Option pricing under path-dependent stock models," Papers 2211.10953, arXiv.org, revised Aug 2023.
    4. Tomonori Nakatsu, 2019. "Some Properties of Density Functions on Maxima of Solutions to One-Dimensional Stochastic Differential Equations," Journal of Theoretical Probability, Springer, vol. 32(4), pages 1746-1779, December.
    5. Arturo Kohatsu & Montero Miquel, 2003. "Malliavin calculus in finance," Economics Working Papers 672, Department of Economics and Business, Universitat Pompeu Fabra.
    6. Muroi, Yoshifumi & Suda, Shintaro, 2017. "Computation of Greeks in jump-diffusion models using discrete Malliavin calculus," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 140(C), pages 69-93.
    7. Tomonori Nakatsu, 2017. "An Integration by Parts Type Formula for Stopping Times and its Application," Methodology and Computing in Applied Probability, Springer, vol. 19(3), pages 751-773, September.
    8. Hideharu Funahashi & Masaaki Kijima, 2016. "Analytical pricing of single barrier options under local volatility models," Quantitative Finance, Taylor & Francis Journals, vol. 16(6), pages 867-886, June.
    9. Dorival Le~ao & Alberto Ohashi & Vinicius Siqueira, 2013. "A general Multidimensional Monte Carlo Approach for Dynamic Hedging under stochastic volatility," Papers 1308.1704, arXiv.org, revised Aug 2013.
    10. Nicola Cufaro Petroni & Piergiacomo Sabino, 2013. "Multidimensional quasi-Monte Carlo Malliavin Greeks," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 36(2), pages 199-224, November.
    11. Guangwu Liu & L. Jeff Hong, 2011. "Kernel Estimation of the Greeks for Options with Discontinuous Payoffs," Operations Research, INFORMS, vol. 59(1), pages 96-108, February.
    12. Shaolong Tong & Guangwu Liu, 2016. "Importance Sampling for Option Greeks with Discontinuous Payoffs," INFORMS Journal on Computing, INFORMS, vol. 28(2), pages 223-235, May.
    13. Wang, Chuan-Ju & Kao, Ming-Yang, 2016. "Optimal search for parameters in Monte Carlo simulation for derivative pricing," European Journal of Operational Research, Elsevier, vol. 249(2), pages 683-690.

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