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Evaluating Value-at-Risk Models with Desk-Level Data

Author

Listed:
  • Jeremy Berkowitz

    (Department of Finance, University of Houston, Houston, Texas 77004)

  • Peter Christoffersen

    (McGill University, Montreal, Quebec H3A 2T5, Canada; and CREATES, School of Economics and Management, University of Aarhus, DK-8000 Aarhus C, Denmark)

  • Denis Pelletier

    (Department of Economics, College of Management, North Carolina State University, Raleigh, North Carolina 27695)

Abstract

We present new evidence on disaggregated profit and loss (P/L) and value-at-risk (VaR) forecasts obtained from a large international commercial bank. Our data set includes the actual daily P/L generated by four separate business lines within the bank. All four business lines are involved in securities trading and each is observed daily for a period of at least two years. Given this unique data set, we provide an integrated, unifying framework for assessing the accuracy of VaR forecasts. We use a comprehensive Monte Carlo study to assess which of these many tests have the best finite-sample size and power properties. Our desk-level data set provides importance guidance for choosing realistic P/L-generating processes in the Monte Carlo comparison of the various tests. The conditional autoregressive value-at-risk test of Engle and Manganelli (2004) performs best overall, but duration-based tests also perform well in many cases. This paper was accepted by John Birge, focused issue editor.

Suggested Citation

  • Jeremy Berkowitz & Peter Christoffersen & Denis Pelletier, 2011. "Evaluating Value-at-Risk Models with Desk-Level Data," Management Science, INFORMS, vol. 57(12), pages 2213-2227, December.
    • Handle: RePEc:inm:ormnsc:v:57:y:2011:i:12:p:2213-2227
    DOI: 10.1287/mnsc.1080.0964
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    More about this item

    Keywords

    risk management; backtesting; volatility; disclosure;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • 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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