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The Pernicious Effects of Contaminated Data in Risk Management

43 Pages Posted: 15 Jan 2010 Last revised: 14 Mar 2013

Laurent Frésard

University of Maryland - Robert H. Smith School of Business

Christophe Perignon

HEC Paris - Finance Department

Anders Wilhelmsson

Lund University - Department of Economics

Date Written: February 11, 2011

Abstract

Banks hold capital to guard against unexpected surges in losses and long freezes in financial markets. The minimum level of capital is set by banking regulators as a function of the banks’ own estimates of their risk exposures. As a result, a great challenge for both banks and regulators is to validate internal risk models. We show that a large fraction of US and international banks uses contaminated data when testing their models. In particular, most banks validate their market risk model using profit-and-loss (P/L) data that include fees and commissions and intraday trading revenues. This practice is inconsistent with the definition of the employed market risk measure. Using both bank data and simulations, we find that data contamination has dramatic implications for model validation and can lead to the acceptance of misspecified risk models. Moreover, our estimates suggest that the use of contaminated data can significantly reduce (market-risk induced) regulatory capital.

Keywords: Regulatory capital, proprietary trading, backtesting, value-at-risk, profit-and-loss

JEL Classification: G21, G28, G32

Suggested Citation

Frésard, Laurent and Perignon, Christophe and Wilhelmsson, Anders, The Pernicious Effects of Contaminated Data in Risk Management (February 11, 2011). Available at SSRN: https://ssrn.com/abstract=1537244 or http://dx.doi.org/10.2139/ssrn.1537244

Laurent Frésard

University of Maryland - Robert H. Smith School of Business ( email )

College Park, MD 20742-1815
United States

Christophe Perignon (Contact Author)

HEC Paris - Finance Department ( email )

1 rue de la Liberation
Jouy-en-Josas Cedex, 78351
France

Anders Wilhelmsson

Lund University - Department of Economics ( email )

Lund
Sweden

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