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Value-at-Risk in turbulence time

Author

Listed:
  • Genest, Benoit
  • Cao, Zhili

Abstract

Value-at-Risk (VaR) has been adopted as the cornerstone and common language of risk management by virtually all major financial institutions and regulators. However, this risk measure has failed to warn the market participants during the financial crisis. In this paper, we show this failure may come from the methodology that we use to calculate VaR and not necessarily for VaR measure itself. we compare two different methods for VaR calculation, 1. by assuming the normal distribution of portfolio return, 2. by using a bootstrap method in a nonparametric framework. The Empirical exercise is implemented on CAC40 index, and the results show us that the first method will underestimate the market risk - the failure of VaR measure occurs. Yet, the second method overcomes the shortcomings of the first method and provides results that pass the tests of VaR evaluation.

Suggested Citation

  • Genest, Benoit & Cao, Zhili, 2014. "Value-at-Risk in turbulence time," MPRA Paper 62906, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:62906
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    References listed on IDEAS

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    6. 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.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Value-at-risk; GARCH model; Bootstrap; hit function; VaR evaluation.;
    All these keywords.

    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G1 - Financial Economics - - General Financial Markets

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