IDEAS home Printed from https://ideas.repec.org/p/bca/bocawp/13-47.html
   My bibliography  Save this paper

CoMargin

Author

Listed:
  • Selma Chaker
  • Nour Meddahi

Abstract

We present CoMargin, a new methodology to estimate collateral requirements for central counterparties (CCPs) in derivatives markets. CoMargin depends on both the tail risk of a given market participant and its interdependence with other participants. Our approach internalizes market interdependencies and enhances the stability of CCPs, thereby reducing the systemic risk concerns associated with them. CoMargin can be estimated using a model-free and scenario-based methodology, validated using formal statistical tests, and generalized to any number of market participants. We assess and illustrate our methodology using proprietary data from the Canadian Derivatives Clearing Corporation (CDCC). Our data set, the first one of its kind to be used in an academic study, includes daily observations of the actual trading positions of all CDCC members from 2003 to 2011. We show theoretically and empirically that CoMargin outperforms existing margining systems by stabilizing the probability and minimizing the shortfall of simultaneous margin-exceeding losses. The relative performance of our methodology increases when trading similarities across clearing members or co-movements among underlying assets increase, as was the case during the recent financial crisis.

Suggested Citation

  • Selma Chaker & Nour Meddahi, 2013. "CoMargin," Staff Working Papers 13-47, Bank of Canada.
  • Handle: RePEc:bca:bocawp:13-47
    as

    Download full text from publisher

    File URL: https://www.bankofcanada.ca/wp-content/uploads/2013/12/wp2013-47.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Paul H. Kupiec, 1994. "The performance of S&P 500 futures product margins under the SPAN margining system," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 14(7), pages 789-811, October.
    2. Rafael Schmidt & Ulrich Stadtmüller, 2006. "Non‐parametric Estimation of Tail Dependence," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(2), pages 307-335, June.
    3. Jeremy Berkowitz & James O'Brien, 2002. "How Accurate Are Value‐at‐Risk Models at Commercial Banks?," Journal of Finance, American Finance Association, vol. 57(3), pages 1093-1111, June.
    4. Markus K. Brunnermeier & Lasse Heje Pedersen, 2009. "Market Liquidity and Funding Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 22(6), pages 2201-2238, June.
    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. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    7. Barry Arnold & Robert Beaver & Richard Groeneveld & William Meeker, 1993. "The nontruncated marginal of a truncated bivariate normal distribution," Psychometrika, Springer;The Psychometric Society, vol. 58(3), pages 471-488, September.
    8. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    9. Kee-Hong Bae & G. Andrew Karolyi & René M. Stulz, 2003. "A New Approach to Measuring Financial Contagion," The Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 717-763, July.
    10. Jeremy Berkowitz & Peter Christoffersen & Denis Pelletier, 2011. "Evaluating Value-at-Risk Models with Desk-Level Data," Management Science, INFORMS, vol. 57(12), pages 2213-2227, December.
    11. Duffie, Darrell & Li, Ada & Lubke, Theo, 2010. "Policy Perspectives on OTC Derivatives Market Infrastructure," Research Papers 2046, Stanford University, Graduate School of Business.
    12. Francis A. Longstaff, 2004. "The Flight-to-Liquidity Premium in U.S. Treasury Bond Prices," The Journal of Business, University of Chicago Press, vol. 77(3), pages 511-526, July.
    13. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    14. Horrace, William C., 2005. "Some results on the multivariate truncated normal distribution," Journal of Multivariate Analysis, Elsevier, vol. 94(1), pages 209-221, May.
    15. Stephen Figlewski, 1984. "Margins and market integrity: Margin setting for stock index futures and options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 4(3), pages 385-416, September.
    16. Nicole M. Boyson & Christof W. Stahel & René M. Stulz, 2010. "Hedge Fund Contagion and Liquidity Shocks," Journal of Finance, American Finance Association, vol. 65(5), pages 1789-1816, October.
    17. Theo Lubke & Ada Li & Darrell Duffie, 2010. "Policy perspectives on OTC derivatives market infrastructure," Staff Reports 424, Federal Reserve Bank of New York.
    18. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    19. G. Geoffrey Booth & John Paul Broussard & Teppo Martikainen & Vesa Puttonen, 1997. "Prudent Margin Levels in the Finnish Stock Index Futures Market," Management Science, INFORMS, vol. 43(8), pages 1177-1188, August.
    20. Cotter, John, 2001. "Margin exceedences for European stock index futures using extreme value theory," Journal of Banking & Finance, Elsevier, vol. 25(8), pages 1475-1502, August.
    21. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    22. Ser-Huang Poon, 2004. "Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications," The Review of Financial Studies, Society for Financial Studies, vol. 17(2), pages 581-610.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cruz Lopez, Jorge A. & Harris, Jeffrey H. & Hurlin, Christophe & Pérignon, Christophe, 2017. "CoMargin," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(5), pages 2183-2215, October.
      • Jorge A. Cruz Lopez & Jeffrey H. Harris & Christophe Hurlin & Christophe Pérignon, 2015. "CoMargin," Working Papers halshs-00979440, HAL.
      • Jorge Cruz Lopez & Jeffrey Harris & Christophe Hurlin & Christophe Pérignon, 2017. "CoMargin," Post-Print hal-03579309, HAL.
    2. Colletaz, Gilbert & Hurlin, Christophe & Pérignon, Christophe, 2013. "The Risk Map: A new tool for validating risk models," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3843-3854.
    3. 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.
    4. Christophe Hurlin & Christophe Pérignon, 2012. "Margin Backtesting," Working Papers halshs-00746274, HAL.
    5. Denisa Banulescu-Radu & Christophe Hurlin & Jérémy Leymarie & Olivier Scaillet, 2021. "Backtesting Marginal Expected Shortfall and Related Systemic Risk Measures," Management Science, INFORMS, vol. 67(9), pages 5730-5754, September.
    6. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    7. 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.
    8. Lazar, Emese & Zhang, Ning, 2019. "Model risk of expected shortfall," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 74-93.
    9. Steven Kou & Xianhua Peng, 2016. "On the Measurement of Economic Tail Risk," Operations Research, INFORMS, vol. 64(5), pages 1056-1072, October.
    10. Francine Gresnigt & Erik Kole & Philip Hans Franses, 2017. "Exploiting Spillovers to Forecast Crashes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(8), pages 936-955, December.
    11. Alexander, Carol & Kaeck, Andreas & Sumawong, Anannit, 2019. "A parsimonious parametric model for generating margin requirements for futures," European Journal of Operational Research, Elsevier, vol. 273(1), pages 31-43.
    12. Zhang, Bangzheng & Wei, Yu & Yu, Jiang & Lai, Xiaodong & Peng, Zhenfeng, 2014. "Forecasting VaR and ES of stock index portfolio: A Vine copula method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 112-124.
    13. Chen, Yi-Hsuan & Tu, Anthony H., 2013. "Estimating hedged portfolio value-at-risk using the conditional copula: An illustration of model risk," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 514-528.
    14. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    15. Elena-Ivona Dumitrescu & Christophe Hurlin & Vinson Pham, 2012. "Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests," Finance, Presses universitaires de Grenoble, vol. 33(1), pages 79-112.
    16. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
    17. Berens, Tobias & Weiß, Gregor N.F. & Wied, Dominik, 2015. "Testing for structural breaks in correlations: Does it improve Value-at-Risk forecasting?," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 135-152.
    18. Torben G. Andersen & Tim Bollerslev & Peter Christoffersen & Francis X. Diebold, 2007. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Chapters, in: The Risks of Financial Institutions, pages 513-544, National Bureau of Economic Research, Inc.
    19. Ye, Wuyi & Luo, Kebing & Liu, Xiaoquan, 2017. "Time-varying quantile association regression model with applications to financial contagion and VaR," European Journal of Operational Research, Elsevier, vol. 256(3), pages 1015-1028.
    20. Vincenzo Candila, 2013. "A Comparison of the Forecasting Performances of Multivariate Volatility Models," Working Papers 3_228, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno.

    More about this item

    Keywords

    Econometric and statistical methods; Financial Institutions; Financial markets; Financial stability;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bca:bocawp:13-47. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/bocgvca.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.