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Stress-testing U.S. bank holding companies: a dynamic panel quantile regression approach

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  • Francisco B. Covas
  • Ben Rump
  • Egon Zakrajsek

Abstract

We propose an econometric framework for estimating capital shortfalls of bank holding companies (BHCs) under pre-specified macroeconomic scenarios. To capture the nonlinear dynamics of bank losses and revenues during periods of financial stress, we use a fixed effects quantile autoregressive (FE-QAR) model with exogenous macroeconomic covariates, an approach that delivers a superior out-of-sample forecasting performance compared with the standard linear framework. According to the out-of-sample forecasts, the realized net charge-offs during the 2007-09 crisis are within the multi-step-ahead density forecasts implied by the FE-QAR model, but they are frequently outside the density forecasts generated using the corresponding linear model. This difference reflects the fact that the linear specification substantially underestimates loan losses, especially for real estate loan portfolios. Employing the macroeconomic stress scenario used in CCAR 2012, we use the density forecasts generated by the FE-QAR model to simulate capital shortfalls for a panel of large BHCs. For almost all institutions in the sample, the FE-QAR model generates capital shortfalls that are considerably higher than those implied by its linear counterpart, which suggests that our approach has the potential for detecting emerging vulnerabilities in the financial system.

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Bibliographic Info

Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series Finance and Economics Discussion Series with number 2013-55.

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Date of creation: 2013
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Handle: RePEc:fip:fedgfe:2013-55

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  1. Simon Gilchrist & Vladimir Yankov & Egon Zakrajsek, 2009. "Credit Market Shocks and Economic Fluctuations: Evidence from Corporate Bond and Stock Markets," NBER Working Papers 14863, National Bureau of Economic Research, Inc.
  2. González-Rivera, Gloria & Yoldas, Emre, 2012. "Autocontour-based evaluation of multivariate predictive densities," International Journal of Forecasting, Elsevier, vol. 28(2), pages 328-342.
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  5. Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2013. "Dynamic effects of credit shocks in a data-rich environment," Staff Reports 615, Federal Reserve Bank of New York.
  6. Schechtman, Ricardo & Gaglianone, Wagner Piazza, 2012. "Macro stress testing of credit risk focused on the tails," Journal of Financial Stability, Elsevier, vol. 8(3), pages 174-192.
  7. Marco Sorge, 2004. "Stress-testing financial systems: an overview of current methodologies," BIS Working Papers 165, Bank for International Settlements.
  8. Jonah B. Gelbach & Doug Miller, 2009. "Robust Inference with Multi-way Clustering," Working Papers 99, University of California, Davis, Department of Economics.
  9. Martin Cihák, 2007. "Introduction to Applied Stress Testing," IMF Working Papers 07/59, International Monetary Fund.
  10. William B. English & William R. Nelson, 1998. "Profits and balance sheet developments at U.S. commercial banks in 1997," Federal Reserve Bulletin, Board of Governors of the Federal Reserve System (U.S.), issue Jun, pages 391-419.
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  12. Antonella Foglia, 2009. "Stress Testing Credit Risk: A Survey of Authorities' Aproaches," International Journal of Central Banking, International Journal of Central Banking, vol. 5(3), pages 9-45, September.
  13. Anthony Tay & Kenneth F. Wallis, 2000. "Density Forecasting: A Survey," Econometric Society World Congress 2000 Contributed Papers 0370, Econometric Society.
  14. Koenker, Roger, 2004. "Quantile regression for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 74-89, October.
  15. Lamarche, Carlos, 2010. "Robust penalized quantile regression estimation for panel data," Journal of Econometrics, Elsevier, vol. 157(2), pages 396-408, August.
  16. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
  17. Wagner Piazza Gaglianone & Luiz Renato Lima, 2012. "Constructing Density Forecasts from Quantile Regressions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(8), pages 1589-1607, December.
  18. Sorge, Marco & Virolainen, Kimmo, 2006. "A comparative analysis of macro stress-testing methodologies with application to Finland," Journal of Financial Stability, Elsevier, vol. 2(2), pages 113-151, June.
  19. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-83, November.
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