How Accurate Are Value-at-Risk Models at Commercial Banks?


  • Jeremy Berkowitz,

  • James O'Brien

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    • Berkowitz is from the University of California, Irvine and O'Brien is from the Federal Reserve Board. We gratefully acknowledge the support and comments of Denise Dittrich, Jim Embersit, Mike Gibson, Philippe Jorion, Matt Pritsker, Hao Zhou, and colleagues at the Federal Reserve Board and the New York Fed. The comments and suggestions of an anonymous referee were especially helpful in improving the paper. The opinions expressed do not necessarily represent those of the Federal Reserve Board or its staff.


In recent years, the trading accounts at large commercial banks have grown substantially and become progressively more diverse and complex. We provide descriptive statistics on the trading revenues from such activities and on the associated Value-at-Risk (VaR) forecasts internally estimated by banks. For a sample of large bank holding companies, we evaluate the performance of banks trading risk models by examining the statistical accuracy of the VaR forecasts. Although a substantial literature has examined the statistical and economic meaning of Value-at-Risk models, this article is the first to provide a detailed analysis of the performance of models actually in use.