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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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    Citations

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    Cited by:

    1. Andrey Bedin & Alexander Kulikov & Andrey Polbin, 2023. "Copula-Based Modelling of Relationship Between Dollar/Rouble Exchange Rate and Oil Prices," Russian Journal of Money and Finance, Bank of Russia, vol. 82(3), pages 87-109, September.
    2. 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.
    3. 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.
    4. 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.
    5. 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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