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Interest Rate Risk Management Based on Copula-GARCH Models

Author

Listed:
  • Penikas, Henry

    (Higher School of Economics, Russia)

  • Simakova, Varvara

    (Higher School of Economics, Russia)

Abstract

The paper is aimed at making comparative analysis of main market risk features based on the copula-modeling and on the traditional approach which neglects the asymmetry and the fat tails of interest rates joint multivariate distribution. R software is used for practical implementation of the introduced methodology when dealing with copulas.Copula application makes it possible to reveal that the interest rates joint multivariate distribution is asymmetric, i.e. interest rates tend more frequently to rise simultaneously, than to decline. It is also shown that copulas help diminish the expected value of equity-at-risk breaches by 7–13% depending on the chosen confidence level

Suggested Citation

  • Penikas, Henry & Simakova, Varvara, 2009. "Interest Rate Risk Management Based on Copula-GARCH Models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 13(1), pages 3-36.
  • Handle: RePEc:ris:apltrx:0026
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    References listed on IDEAS

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    1. Dean Fantazzini, 2008. "Dynamic Copula Modelling for Value at Risk," Frontiers in Finance and Economics, SKEMA Business School, vol. 5(2), pages 72-108, October.
    2. Chollete, Lorán & Heinen, Andreas, 2006. "Frequent Turbulence? A Dynamic Copula Approach," Discussion Papers 2006/10, Norwegian School of Economics, Department of Business and Management Science.
    3. Fantazzini , Dean, 2009. "Econometric Analysis of Financial Data in Risk Management," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 14(2), pages 100-127.
    4. Kole, Erik & Koedijk, Kees & Verbeek, Marno, 2007. "Selecting copulas for risk management," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2405-2423, August.
    5. Junker, Markus & Szimayer, Alex & Wagner, Niklas, 2006. "Nonlinear term structure dependence: Copula functions, empirics, and risk implications," Journal of Banking & Finance, Elsevier, vol. 30(4), pages 1171-1199, April.
    6. Rosenberg, Joshua V. & Schuermann, Til, 2006. "A general approach to integrated risk management with skewed, fat-tailed risks," Journal of Financial Economics, Elsevier, vol. 79(3), pages 569-614, March.
    7. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    8. Qiang Dai & Kenneth J. Singleton, 2000. "Specification Analysis of Affine Term Structure Models," Journal of Finance, American Finance Association, vol. 55(5), pages 1943-1978, October.
    9. Vasicek, Oldrich, 1977. "An equilibrium characterization of the term structure," Journal of Financial Economics, Elsevier, vol. 5(2), pages 177-188, November.
    10. Thierry Ane & Cecile Kharoubi, 2003. "Dependence Structure and Risk Measure," The Journal of Business, University of Chicago Press, vol. 76(3), pages 411-438, July.
    11. De Pooter, Michiel & Ravazzolo, Francesco & van Dijk, Dick, 2006. "Predicting the term structure of interest rates incorporating parameter uncertainty, model uncertainty and macroeconomic information," MPRA Paper 2512, University Library of Munich, Germany, revised 03 Mar 2007.
    12. Robert T. Clemen & Terence Reilly, 1999. "Correlations and Copulas for Decision and Risk Analysis," Management Science, INFORMS, vol. 45(2), pages 208-224, February.
    13. François, LONGIN & Bruno, SOLNIK, 1998. "Correlation Structure of International Equity Markets During Extremely Volatile Periods," HEC Research Papers Series 646, HEC Paris.
    14. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-489, October.
    15. Darrell Duffie & Rui Kan, 1996. "A Yield‐Factor Model Of Interest Rates," Mathematical Finance, Wiley Blackwell, vol. 6(4), pages 379-406, October.
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    Cited by:

    1. Penikas, Henry, 2014. "Investment portfolio risk modelling based on hierarchical copulas," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 35(3), pages 18-38.
    2. Петрова Екатерина Александровна, 2014. "Оценка Риска Остаточной Стоимости Секьюритизированного Пула Активов Оперативного Лизинга," Вестник Финансового университета, CyberLeninka;Федеральное государственное образовательное бюджетное учреждение высшего профессионального образования «Финансовый университет при Правительстве Российской Федерации» (Финансовый университет), issue 3, pages 127-138.
    3. Brodsky, Boris & Penikas, Henry & Safaryan, Irina, 2009. "Detection of Structural Breaks in Copula Models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 16(4), pages 3-15.
    4. Aivazian, Sergei & Afanasiev, Mikhail & Rudenko, Victoria, 2014. "Analysis of dependence between the random components of a stochastic production function for the purpose of technical efficiency estimation," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 34(2), pages 3-18.

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    More about this item

    Keywords

    copula; EVEaR; interest rate risk; Russia; MosPrime; OFZ; yield curve;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • 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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