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Copula-Models in Foreign Exchange Risk-Management of a Bank

Author

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  • Penikas, Henry

    (Higher School of Economics, Russia)

Abstract

The paper deals with the optimization problem aiming to maximize the expected return given the amount of the bank’s open currency positions subject to the level of foreign exchange risk. The goal of the paper is to compare the efficiency of problem-solving assuming either multivariate normality, or using copulas to semi-parametrically simulate the empirical joint distribution. Back-testing is used both to support the choice of a proper copula‑model and to compare the different optimization approaches efficiency. Based on the research results it is shown that copula‑models should be preferred as enabling to receive higher yield given the same level of foreign exchange risk

Suggested Citation

  • Penikas, Henry, 2010. "Copula-Models in Foreign Exchange Risk-Management of a Bank," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 17(1), pages 62-87.
  • Handle: RePEc:ris:apltrx:0045
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    References listed on IDEAS

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    1. David A. Hennessy & Harvey E. Lapan, 2002. "The Use of Archimedean Copulas to Model Portfolio Allocations," Mathematical Finance, Wiley Blackwell, vol. 12(2), pages 143-154, April.
    2. Alexandre Adam & Mohamed Houkari & Jean-Paul Laurent, 2007. "Spectral risk measures and portfolio selection," Working Papers hal-00165641, HAL.
    3. Merton, Robert C., 1971. "Optimum consumption and portfolio rules in a continuous-time model," Journal of Economic Theory, Elsevier, vol. 3(4), pages 373-413, December.
    4. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    5. Fantazzini, Dean, 2009. "The effects of misspecified marginals and copulas on computing the value at risk: A Monte Carlo study," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2168-2188, April.
    6. Paul A. Samuelson, 2011. "Lifetime Portfolio Selection by Dynamic Stochastic Programming," World Scientific Book Chapters, in: Leonard C MacLean & Edward O Thorp & William T Ziemba (ed.), THE KELLY CAPITAL GROWTH INVESTMENT CRITERION THEORY and PRACTICE, chapter 31, pages 465-472, World Scientific Publishing Co. Pte. Ltd..
    7. Merton, Robert C, 1969. "Lifetime Portfolio Selection under Uncertainty: The Continuous-Time Case," The Review of Economics and Statistics, MIT Press, vol. 51(3), pages 247-257, August.
    8. Markowitz, Harry M, 1991. "Foundations of Portfolio Theory," Journal of Finance, American Finance Association, vol. 46(2), pages 469-477, June.
    9. Kim, Gunky & Silvapulle, Mervyn J. & Silvapulle, Paramsothy, 2007. "Comparison of semiparametric and parametric methods for estimating copulas," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2836-2850, March.
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    Cited by:

    1. E. Petrova A. & Е. Петрова А., 2014. "Оценка Риска Остаточной Стоимости Секьюритизированного Пула Активов Оперативного Лизинга // A Securitized Pool Of Operating Lease Assets And Its Residual Value Risk Evaluation," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, issue 3, pages 127-138.

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    More about this item

    Keywords

    Copulas; foreign exchange risk; open currency position (OCP); optimization;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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