Peter Christoffersen () (McGill University and CREATES) Jeremy Berkowitz () (University of Houston) Denis Pelletier () (North Carolina State University)
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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 dataset 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 dataset, 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 CaViaR test of Engle and Manganelli (2004) performs best overall but duration-based tests also perform well in many cases.
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Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number
2009-35.
Find related papers by JEL classification: G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Mortgages G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Capital and Ownership Structure
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Christoffersen, Peter F, 1998.
"Evaluating Interval Forecasts,"
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-62, November.
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