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Extreme Spectral Risk Measures: An Application to Futures Clearinghouse Margin Requirements

Author

Listed:
  • John Cotter

    (University College Dublin, Ireland)

  • Kevin Dowd

    (The University of Nottingham, UK)

Abstract

This paper applies the Extreme-Value (EV) Generalised Pareto distribution to the extreme tails of the return distributions for the S&P500, FT100, DAX, Hang Seng, and Nikkei225 futures contracts. It then uses tail estimators from these contracts to estimate spectral risk measures, which are coherent risk measures that reflect a user’s risk-aversion function. It compares these to VaR and Expected Shortfall (ES) risk measures, and compares the precision of their estimators. It also discusses the usefulness of these risk measures in the context of clearinghouses setting initial margin requirements, and compares these to the SPAN measures typically used.

Suggested Citation

  • John Cotter & Kevin Dowd, 2011. "Extreme Spectral Risk Measures: An Application to Futures Clearinghouse Margin Requirements," Working Papers 200516, Geary Institute, University College Dublin.
  • Handle: RePEc:ucd:wpaper:2005/16
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. John Cotter & Kevin Dowd, 2010. "Estimating financial risk measures for futures positions: A nonparametric approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 30(7), pages 689-703, July.
    2. repec:hal:journl:halshs-00969242 is not listed on IDEAS
    3. Henryk Gzyl & Silvia Mayoral, 2006. "On a relationship between distorted and spectral risk measures," Faculty Working Papers 15/06, School of Economics and Business Administration, University of Navarra.
    4. Cotter, John & Dowd, Kevin, 2007. "Evaluating the Precision of Estimators of Quantile-Based Risk Measures," MPRA Paper 3504, University Library of Munich, Germany.
    5. Robert A. Jones & Christophe Pérignon, 2013. "Derivatives Clearing, Default Risk, and Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(2), pages 373-400, June.
    6. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    7. Kevin Dowd & John Cotter & Ghulam Sorwar, 2008. "Spectral Risk Measures: Properties and Limitations," Journal of Financial Services Research, Springer;Western Finance Association, vol. 34(1), pages 61-75, August.
    8. Cotter, John & Dowd, Kevin, 2006. "Spectral Risk Measures with an Application to Futures Clearinghouse Variation Margin Requirements," MPRA Paper 3495, University Library of Munich, Germany.
    9. John Cotter & Kevin Dowd, 2011. "Intra-Day Seasonality in Foreign Market Transactions," Working Papers 200744, Geary Institute, University College Dublin.
    10. Rodrigo Herrera & Bernhard Schipp, 2011. "Extreme value models in a conditional duration intensity framework," SFB 649 Discussion Papers SFB649DP2011-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Dominique Guegan & Bertrand Hassani, 2014. "Distortion Risk Measures or the Transformation of Unimodal Distributions into Multimodal Functions," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00969242, HAL.
    12. Ibragimov, Rustam & Walden, Johan, 2007. "The limits of diversification when losses may be large," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2551-2569, August.
    13. John Cotter & Richard Roll, 2010. "A Comparative Anatomy of REITs and Residential Real Estate Indexes: Returns, Risks and Distributional Characteristics," Working Papers 201008, Geary Institute, University College Dublin.
    14. Wächter, Hans Peter & Mazzoni, Thomas, 2013. "Consistent modeling of risk averse behavior with spectral risk measures," European Journal of Operational Research, Elsevier, vol. 229(2), pages 487-495.
    15. Ibragimov, Rustam & Walden, Johan, 2007. "The limits of diversification when losses may be large," Scholarly Articles 2624460, Harvard University Department of Economics.
    16. Mario Brandtner, 2016. "Spektrale Risikomaße: Konzeption, betriebswirtschaftliche Anwendungen und Fallstricke," Management Review Quarterly, Springer;Vienna University of Economics and Business, vol. 66(2), pages 75-115, April.
    17. Takashi Kato, 2017. "Asymptotic Analysis for Spectral Risk Measures Parameterized by Confidence Level," Papers 1711.07335, arXiv.org.
    18. Tolikas, Konstantinos & Gettinby, Gareth D., 2009. "Modelling the distribution of the extreme share returns in Singapore," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 254-263, March.
    19. Marcin Fałdziński & Magdalena Osińska & Tomasz Zdanowicz, 2012. "Detecting Risk Transfer in Financial Markets using Different Risk Measures," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 4(1), pages 45-64, March.
    20. Douglas D. Evanoff & Daniela Russo & Robert Steigerwald, 2006. "Policymakers, researchers, and practitioners discuss the role of central counterparties," Economic Perspectives, Federal Reserve Bank of Chicago, issue Q IV, pages 2-21.
    21. Alexandru Stanga, 2008. "Measuring market risk: a copula and extreme value approach," Advances in Economic and Financial Research - DOFIN Working Paper Series 13, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB.
    22. Cotter, John, 2007. "Extreme risk in Asian equity markets," MPRA Paper 3536, University Library of Munich, Germany.

    More about this item

    Keywords

    Spectral risk measures; Expected Shortfall; Value at Risk; Extreme Value; clearinghouse;

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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