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Measuring Event Risk

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  • Peter Nyberg
  • Anders Wilhelmsson

Abstract

This paper decomposes the popular risk measure Value-at-Risk (VaR) into one jump- and one continuous component. The continuous component corresponds to general market risk and the jump component is proportional to the event risk as defined in the Basel II accord. We find that event risk, which is currently not incorporated into most banks' VaR models, comprises a substantial part of total VaR. It constitutes 30% of the risk for a portfolio of small cap stocks but less than 1% for a portfolio of large cap stocks. The national supervising agency in each membership country is advised by the Basel rules to add an additional capital charge to a bank whose models do not capture event risk. The large variation in event risk, also found across 10 individual stocks, suggests that an approach that varies the capital surcharge, based on the type of asset, should be used by the supervisors. Copyright The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.

Suggested Citation

  • Peter Nyberg & Anders Wilhelmsson, 2009. "Measuring Event Risk," Journal of Financial Econometrics, Oxford University Press, vol. 7(3), pages 265-287, Summer.
    • Handle: RePEc:oup:jfinec:v:7:y:2009:i:3:p:265-287
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbp003
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    Cited by:

    1. Jan Hanousek & Evžen Kočenda & Jan Novotný, 2016. "Shluková analýza skoků na kapitálových trzích [Cluster Analysis of Jumps on Capital Markets]," Politická ekonomie, Prague University of Economics and Business, vol. 2016(2), pages 127-144.
    2. Zhou, Chunyang & Wu, Chongfeng & Wang, Yudong, 2019. "Dynamic portfolio allocation with time-varying jump risk," Journal of Empirical Finance, Elsevier, vol. 50(C), pages 113-124.
    3. Chunyang Zhou & Chongfeng Wu & Weidong Xu, 2020. "Incorporating time‐varying jump intensities in the mean‐variance portfolio decisions," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(3), pages 460-478, March.
    4. Hanousek Jan & Kočenda Evžen & Novotný Jan, 2012. "The identification of price jumps," Monte Carlo Methods and Applications, De Gruyter, vol. 18(1), pages 53-77, January.
    5. Jan Novotn?? & Jan Hanousek & Ev??en Ko??enda, 2013. "Price Jump Indicators: Stock Market Empirics During the Crisis," William Davidson Institute Working Papers Series wp1050, William Davidson Institute at the University of Michigan.

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