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Early Detection Techniques for Market Risk Failure

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  • Olmo Jose

    ()
    (Centro Universitario de la Defensa de Zaragoza and City University London)

  • Pouliot William

    ()
    (University of Liverpool)

Abstract

The implementation of appropriate statistical techniques (backtesting) for monitoring conditional VaR models is the mechanism used by financial institutions to determine the severity of departures of the VaR model from market results and subsequently, the tool used by regulators to determine the penalties imposed for inadequate risk models. So far, however, there has been no attempt to determine the timing of this rejection and with it to obtain some guidance regarding the cause of failure in reporting an appropriate VaR. This paper corrects this by proposing U-statistic type processes that extend standard CUSUM statistics widely employed for change-point detection. In contrast to CUSUM statistics these new tests are indexed by certain weight functions that enhance their statistical power to detect the timing of the market risk model failure. These tests are robust to estimation risk and can be devised to be very sensitive to detection of market failure produced early in the out-of-sample evaluation period, in which standard methods usually fail due to the absence of data.

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Bibliographic Info

Article provided by De Gruyter in its journal Studies in Nonlinear Dynamics & Econometrics.

Volume (Year): 15 (2011)
Issue (Month): 4 (September)
Pages: 1-55

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Handle: RePEc:bpj:sndecm:v:15:y:2011:i:4:n:1

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  1. Gombay Edit & Horváth Lajos & Husková Marie, 1996. "Estimators And Tests For Change In Variances," Statistics & Risk Modeling, De Gruyter, De Gruyter, vol. 14(2), pages 145-160, February.
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Cited by:
  1. Pouliot, W. & Olmo, J., 2008. "U-statistic Type Tests for Structural Breaks in Linear Regression Models," Working Papers, Department of Economics, City University London 08/15, Department of Economics, City University London.

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