Evaluating Value-at-Risk models with desk-level data
AbstractWe present new evidence on disaggregated profit and loss and VaR forecasts obtained from a large international commercial bank. Our dataset includes 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 rich dataset, we provide an integrated, unifying framework for assessing the accuracy of VaR forecasts. A thorough Monte Carlo comparison of the various methods is conducted to provide guidance as to which of these many tests have the best finite-sample size and power properties. 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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Bibliographic InfoPaper provided by North Carolina State University, Department of Economics in its series Working Paper Series with number 010.
Length: 32 pages
Date of creation: Oct 2005
Date of revision: Dec 2006
risk management; backtesting; volatility; disclosure;
Other versions of this item:
- 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.
- Peter Christoffersen & Jeremy Berkowitz & Denis Pelletier, 2008. "Evaluating Value-at-Risk Models with Desk-Level Data," CREATES Research Papers 2009-35, School of Economics and Management, University of Aarhus.
- 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-01-13 (All new papers)
- NEP-BAN-2007-01-13 (Banking)
- NEP-ECM-2007-01-13 (Econometrics)
- NEP-FOR-2007-01-13 (Forecasting)
- NEP-RMG-2007-01-13 (Risk Management)
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