The Pernicious Effects of Contaminated Data in Risk Management

Research output: Contribution to journalArticle

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.

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Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Business Administration
  • Economics

Keywords

  • proprietary trading, Regulatory capital, backtesting, value-at-risk, profit-and-loss
Original languageEnglish
Pages (from-to)2569-2583
JournalJournal of Banking & Finance
Volume35
Issue number10
Publication statusPublished - 2011
Publication categoryResearch
Peer-reviewedYes