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Risk models–at–risk

Author

Listed:
  • Boucher, Christophe M.
  • Danielsson, Jon
  • Kouontchou, Patrick S.
  • Maillet, Bertrand B.
Abstract
The experience from the global financial crisis has raised serious concerns about the accuracy of standard risk measures as tools for the quantification of extreme downward risk. A key reason for this is that risk measures are subject to model risk due, e.g., to specification and estimation uncertainty. While the authorities would like financial institutions to assess model risk, there is no accepted approach for such computations. We propose a remedy for this by a general framework for the computation of risk measures robust to model risk by empirically adjusting imperfect risk forecasts by outcomes from backtesting, considering the desirable quality of VaR models such as the frequency, independence and magnitude of violations. We also provide a fair comparison between the main risk models using the same metric that corresponds to model risk required corrections.

Suggested Citation

  • Boucher, Christophe M. & Danielsson, Jon & Kouontchou, Patrick S. & Maillet, Bertrand B., 2014. "Risk models–at–risk," LSE Research Online Documents on Economics 59299, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:59299
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    File URL: http://eprints.lse.ac.uk/59299/
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    More about this item

    Keywords

    model risk; value–at–risk; backtesting;
    All these keywords.

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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