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Implied Risk Exposures

Author

Listed:
  • Sylvain Benoît

    (LEO - Laboratoire d'économie d'Orleans [2008-2011] - UO - Université d'Orléans - CNRS - Centre National de la Recherche Scientifique)

  • Christophe Hurlin

    (LEO - Laboratoire d'économie d'Orleans [2008-2011] - UO - Université d'Orléans - CNRS - Centre National de la Recherche Scientifique)

  • Christophe Pérignon

    (GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique)

Abstract

We show how to reverse-engineer banks' risk disclosures, such as Value-at-Risk, to obtain an implied measure of their exposures to equity, interest rate, foreign exchange, and commodity risks. Factor Implied Risk Exposures (FIRE) are obtained by breaking down a change in risk disclosure into a market volatility component and a bank-specific risk exposure component. In a study of large US and international banks, we show that (1) changes in risk exposures are negatively correlated with market volatility and (2) changes in risk exposures are positively correlated across banks, which is consistent with banks exhibiting commonality in trading.

Suggested Citation

  • Sylvain Benoît & Christophe Hurlin & Christophe Pérignon, 2014. "Implied Risk Exposures," Working Papers halshs-00836280, HAL.
  • Handle: RePEc:hal:wpaper:halshs-00836280
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00836280v3
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    References listed on IDEAS

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    1. Pierre Giot & Sébastien Laurent, 2003. "Value-at-risk for long and short trading positions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(6), pages 641-663.
    2. Gomez, Matthieu & Landier, Augustin & Sraer, David & Thesmar, David, 2021. "Banks’ exposure to interest rate risk and the transmission of monetary policy," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 543-570.
    3. Sylvain Benoit & Jean-Edouard Colliard & Christophe Hurlin & Christophe Pérignon, 2017. "Where the Risks Lie: A Survey on Systemic Risk," Review of Finance, European Finance Association, vol. 21(1), pages 109-152.
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    8. Vikas Agarwal & Wei Jiang & Yuehua Tang & Baozhong Yang, 2013. "Uncovering Hedge Fund Skill from the Portfolio Holdings They Hide," Journal of Finance, American Finance Association, vol. 68(2), pages 739-783, April.
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    10. Escanciano, J. Carlos & Olmo, Jose, 2010. "Backtesting Parametric Value-at-Risk With Estimation Risk," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 36-51.
    11. 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.
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    13. Merrill, Craig B. & Nadauld, Taylor & Sherlund, Shane M., 2013. "Why Did Financial Institutions Sell RMBS at Fire Sale Prices during the Financial Crisis?," Working Paper Series 2013-02, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
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    Cited by:

    1. Sylvain Benoit & Jean-Edouard Colliard & Christophe Hurlin & Christophe Pérignon, 2017. "Where the Risks Lie: A Survey on Systemic Risk," Review of Finance, European Finance Association, vol. 21(1), pages 109-152.
    2. de Mendonça, Helder Ferreira & Silva, Rafael Bernardo da, 2018. "Effect of banking and macroeconomic variables on systemic risk: An application of ΔCOVAR for an emerging economy," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 141-157.
    3. Laura Garcia-Jorcano & Lidia Sanchis-Marco, 2023. "Measuring Systemic Risk Using Multivariate Quantile-Located ES Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 1-72.

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    Keywords

    Herding; Risk Disclosure; (Stressed) Value-at-Risk; Regulatory Capital;
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