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Is This Normal? The Cost of Assuming that Derivatives Have Normal Returns

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  • Radoslav Raykov

Abstract

Derivatives exchanges often determine collateral requirements, which are fundamental to market safety, with dated risk models assuming normal returns. However, derivatives returns are heavy-tailed, which leads to the systematic under-collection of collateral (margin). This paper uses extreme value theory (EVT) to evaluate the cost of this margin inadequacy to market participants in the event of default. I find that the Canadian futures market was under-margined by about $1.6 billion during the Great Financial Crisis, and that the default of the highest-impact participant generates a cost of up to $302 million to be absorbed by surviving participants. I show that this cost can consume the market’s entire default fund and result in costly risk mutualization. I advocate for the adoption of EVT as a benchmarking tool and argue that the regulation of exchanges should be revised for financial products with heavy tails.

Suggested Citation

  • Radoslav Raykov, 2024. "Is This Normal? The Cost of Assuming that Derivatives Have Normal Returns," Staff Working Papers 24-46, Bank of Canada.
  • Handle: RePEc:bca:bocawp:24-46
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    References listed on IDEAS

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    1. 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.
    2. Albert J Menkveld, 2017. "Crowded Positions: An Overlooked Systemic Risk for Central Clearing Parties," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 7(2), pages 209-242.
    3. 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.
    4. van Oordt, Maarten R. C. & Zhou, Chen, 2016. "Systematic Tail Risk," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(2), pages 685-705, April.
    5. Mark Paddrik & Sriram Rajan & H. Peyton Young, 2020. "Contagion in Derivatives Markets," Management Science, INFORMS, vol. 66(8), pages 3603-3616, August.
    6. Hall, Peter, 1990. "Using the bootstrap to estimate mean squared error and select smoothing parameter in nonparametric problems," Journal of Multivariate Analysis, Elsevier, vol. 32(2), pages 177-203, February.
    7. Jansen, Dennis W & de Vries, Casper G, 1991. "On the Frequency of Large Stock Returns: Putting Booms and Busts into Perspective," The Review of Economics and Statistics, MIT Press, vol. 73(1), pages 18-24, February.
    8. Huisman, Ronald, et al, 2001. "Tail-Index Estimates in Small Samples," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(2), pages 208-216, April.
    9. François M. Longin, 1999. "Optimal margin level in futures markets: Extreme price movements," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 19(2), pages 127-152, April.
    10. Raykov, Radoslav, 2022. "Systemic Risk and Collateral Adequacy: Evidence from the Futures Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 57(3), pages 1142-1173, May.
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    More about this item

    Keywords

    Financial institutions; Financial stability;

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

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