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Static Hedging of Multivariate Derivatives by Simulation

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  • Paolo Pellizzari

    (University of Venice)

Abstract

We propose an approximate static hedging procedure for multivariate derivatives. The hedging portfolio is composed of statically held simple univariate options, optimally weighted minimizing the variance of the difference between the target claim and the approximate replicating portfolio. The method uses simulated paths to estimate the weights of the hedging portfolio and is related to Monte Carlo control variates techniques. We report numerical results showing the performance of this static hedging procedure on bivariate options on the maximum of two assets and on 2- and 7-dimensional portfolio options. It is shown that, in the presence of transaction costs, Value at Risk and Expected Shortfall of the dynamically hedged positions can be higher than the ones obtained by a static hedge.

Suggested Citation

  • Paolo Pellizzari, 2003. "Static Hedging of Multivariate Derivatives by Simulation," Finance 0311013, University Library of Munich, Germany, revised 04 Dec 2003.
    • Handle: RePEc:wpa:wuwpfi:0311013
    Note: Type of Document - pdf; prepared on Latex on Mac; to print on Laser; pages: 23; figures: included
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    References listed on IDEAS

    as
    1. Leland, Hayne E, 1985. "Option Pricing and Replication with Transactions Costs," Journal of Finance, American Finance Association, vol. 40(5), pages 1283-1301, December.
    2. Stulz, ReneM., 1982. "Options on the minimum or the maximum of two risky assets : Analysis and applications," Journal of Financial Economics, Elsevier, vol. 10(2), pages 161-185, July.
    3. T. Clifton Green & Stephen Figlewski, 1999. "Market Risk and Model Risk for a Financial Institution Writing Options," Journal of Finance, American Finance Association, vol. 54(4), pages 1465-1499, August.
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    7. Hans FÃllmer & Peter Leukert, 2000. "Efficient hedging: Cost versus shortfall risk," Finance and Stochastics, Springer, vol. 4(2), pages 117-146.
    8. Riccardo Rebonato & Ian Cooper, 1998. "Coupling backward induction with Monte Carlo simulations: a fast Fourier transform (FFT) approach," Applied Mathematical Finance, Taylor & Francis Journals, vol. 5(2), pages 131-141.
    9. Barry L. Nelson, 1990. "Control Variate Remedies," Operations Research, INFORMS, vol. 38(6), pages 974-992, December.
    10. repec:bla:jfinan:v:53:y:1998:i:3:p:1165-1190 is not listed on IDEAS
    11. Boyle, Phelim P., 1988. "A Lattice Framework for Option Pricing with Two State Variables," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 23(1), pages 1-12, March.
    12. Boyle, Phelim P. & Emanuel, David, 1980. "Discretely adjusted option hedges," Journal of Financial Economics, Elsevier, vol. 8(3), pages 259-282, September.
    13. Hans FÃllmer & Peter Leukert, 1999. "Quantile hedging," Finance and Stochastics, Springer, vol. 3(3), pages 251-273.
    14. Hyungsok Ahn Adviti & Glen Swindle, 1997. "Misspecified asset price models and robust hedging strategies," Applied Mathematical Finance, Taylor & Francis Journals, vol. 4(1), pages 21-36.
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    Cited by:

    1. Dirk Becherer & Ian Ward, 2010. "Optimal Weak Static Hedging of Equity and Credit Risk Using Derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 17(1), pages 1-28.
    2. Vikranth Lokeshwar & Vikram Bhardawaj & Shashi Jain, 2019. "Neural network for pricing and universal static hedging of contingent claims," Papers 1911.11362, arXiv.org.
    3. Hachmi Ben Ameur & Mouna Boujelbène & J. L. Prigent & Emna Triki, 2020. "Optimal Portfolio Positioning on Multiple Assets Under Ambiguity," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 21-57, June.
    4. Johannes Siven & Rolf Poulsen, 2009. "Auto-static for the people: risk-minimizing hedges of barrier options," Review of Derivatives Research, Springer, vol. 12(3), pages 193-211, October.
    5. Lokeshwar, Vikranth & Bharadwaj, Vikram & Jain, Shashi, 2022. "Explainable neural network for pricing and universal static hedging of contingent claims," Applied Mathematics and Computation, Elsevier, vol. 417(C).

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    More about this item

    Keywords

    Monte Carlo methods; option pricing; static and dynamic hedging;
    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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