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An EVT Approach to calculating Risk Capital Requirements

Author

Listed:
  • Chris Brooks

    (ICMA Centre, University of Reading)

  • Gita Persand

    (ICMA Centre, University of Reading)

  • Andrew D. Clare

    (ICMA Centre, University of Reading)

Abstract

This paper investigates the frequency of extreme events for three LIFFE futures contracts for the calculation of minimum capital risk requirements (MCRRs). We propose a semi-parametric approach where the tails are modelled by the Generalised Pareto Distribution and smaller risks are captured by the empirical distribution function. We compare the capital requirements from this approach with those calculated from the unconditional density and from a conditional density- a GARCH(1,1) model. Our primary finding is that for both in-sample and hold-out samples, our extreme value approach yields superior results than either of the other two models which do not explicitly model the tails of the return distribution. Since the use of these internal models will be permitted under the EC-CAD II, they could be widely adopted in the near future by European financial institutions for determining capital adequacies. Hence, close scrutiny of competing models is required to avoid a potentially costly misallocation of capital resources while at the same time ensuring the safety of the financial system.

Suggested Citation

  • Chris Brooks & Gita Persand & Andrew D. Clare, 2000. "An EVT Approach to calculating Risk Capital Requirements," ICMA Centre Discussion Papers in Finance icma-dp2000-07, Henley Business School, University of Reading.
  • Handle: RePEc:rdg:icmadp:icma-dp2000-07
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    File URL: http://www.icmacentre.ac.uk/pdf/discussion/DP2000-07.pdf
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    References listed on IDEAS

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    1. Brooks, C. & Clare, A. D. & Persand, G., 2000. "A word of caution on calculating market-based minimum capital risk requirements," Journal of Banking & Finance, Elsevier, vol. 24(10), pages 1557-1574, October.
    2. Brock, W.A. & Dechert, W.D. & LeBaron, B. & Scheinkman, J.A., 1995. "A Test for Independence Based on the Correlation Dimension," Working papers 9520, Wisconsin Madison - Social Systems.
    3. Longin, Francois M, 1996. "The Asymptotic Distribution of Extreme Stock Market Returns," The Journal of Business, University of Chicago Press, vol. 69(3), pages 383-408, July.
    4. Hsieh, David A., 1993. "Implications of Nonlinear Dynamics for Financial Risk Management," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(1), pages 41-64, March.
    5. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
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    Cited by:

    1. Rossignolo, Adrian F. & Fethi, Meryem Duygun & Shaban, Mohamed, 2012. "Value-at-Risk models and Basel capital charges," Journal of Financial Stability, Elsevier, vol. 8(4), pages 303-319.
    2. Adrián F. Rossignolo & Víctor A. Álvarez, 2015. "Has the Basel Committee Got it Right? Evidence from Commodity Positions in Turmoil," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 10(1), pages 1-38, Enero-Jun.
    3. Adrián F. Rossignolo & Víctor A. Álvarez, 2015. "Has the Basel Committee Got it Right? Evidence from Commodity Positions in Turmoil," Remef - The Mexican Journal of Economics and Finance, Instituto Mexicano de Ejecutivos de Finanzas. Remef, March.

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    More about this item

    Keywords

    Minimum Capital Risk Requirments; Generalised Pareto Distribution; GARCH models;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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