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Efficient Monte Carlo pricing of European options¶using mean value control variates

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  • P. Pellizzari

Abstract

We describe in this paper a variance reduction method based on control variates. The technique uses the fact that, if all stochastic assets but one are replaced in the payoff function by their mean, the resulting integral can most often be evaluated in closed form. We exploit this idea by applying the univariate payoff as control variate and develop a general Monte Carlo procedure, called Mean Monte Carlo (MMC). The method is then tested on a variety of multifactor options and compared to other Monte Carlo approaches or numerical techniques. The method is of easy and broad applicability and gives good results especially for low to medium dimension and in high volatility environments. Copyright Springer-Verlag Italia 2001

Suggested Citation

  • P. Pellizzari, 2001. "Efficient Monte Carlo pricing of European options¶using mean value control variates," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 24(2), pages 107-126, November.
    • Handle: RePEc:spr:decfin:v:24:y:2001:i:2:p:107-126
    DOI: 10.1007/s102030170002
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    Citations

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    Cited by:

    1. Jérôme Lelong & Zineb El Filali Ech-Chafiq & Adil Reghai, 2020. "Automatic Control Variates for Option Pricing using Neural Networks," Working Papers hal-02891798, HAL.
    2. Georges Dionne & Genevieve Gauthier & Nadia Ouertani & Nabil Tahani, 2011. "Heterogeneous Basket Options Pricing Using Analytical Approximations," Multinational Finance Journal, Multinational Finance Journal, vol. 15(1-2), pages 47-85, March - J.
    3. Jinke Zhou & Xiaolu Wang, 2008. "Accurate closed‐form approximation for pricing Asian and basket options," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(4), pages 343-358, July.
    4. Pellizzari, P., 2005. "Static hedging of multivariate derivatives by simulation," European Journal of Operational Research, Elsevier, vol. 166(2), pages 507-519, October.
    5. Dingeç, Kemal Dinçer & Hörmann, Wolfgang, 2013. "Control variates and conditional Monte Carlo for basket and Asian options," Insurance: Mathematics and Economics, Elsevier, vol. 52(3), pages 421-434.
    6. Jérôme Lelong & Zineb El Filali Ech-Chafiq & Adil Reghai, 2021. "Automatic Control Variates for Option Pricing using Neural Networks," Post-Print hal-02891798, HAL.
    7. Ng, Andrew C.Y. & Li, Johnny Siu-Hang & Chan, Wai-Sum, 2013. "Pricing options on stocks denominated in different currencies: Theory and illustrations," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 339-354.
    8. Leccadito, Arturo & Paletta, Tommaso & Tunaru, Radu, 2016. "Pricing and hedging basket options with exact moment matching," Insurance: Mathematics and Economics, Elsevier, vol. 69(C), pages 59-69.
    9. Hörmann, Wolfgang & Sak, Halis, 2010. "t-Copula generation for control variates," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(4), pages 782-790.

    More about this item

    Keywords

    Mathematics Subject Classification (2000): 65C05; 91B28; Journal of Economic Literature Classification: C15; G12;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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