The Pernicious Effects of Contaminated Data in Risk Management

Christophe Perignon (), Laurent Fresard and Anders Wilhelmsson
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Laurent Fresard: GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique

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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 (search for similar items in EconPapers)
Date: 2011-10
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Citations: View citations in EconPapers (4)

Published in Journal of Banking and Finance, 2011, 35 (10), pp.2569-2583. ⟨10.1016/j.jbankfin.2011.02.013⟩

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Related works:
Journal Article: The pernicious effects of contaminated data in risk management (2011)
Working Paper: The pernicious effects of contaminated data in risk management (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-00630301

DOI: 10.1016/j.jbankfin.2011.02.013

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