IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this paper

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

  • Francisco Covas
  • Ben Rump
  • Egon Zakrajsek

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.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.federalreserve.gov/pubs/feds/2013/201355/201355abs.html
Download Restriction: no

File URL: http://www.federalreserve.gov/pubs/feds/2013/201355/201355pap.pdf
Download Restriction: no

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.

as
in new window

Length:
Date of creation: 2013
Date of revision:
Handle: RePEc:fip:fedgfe:2013-55
Contact details of provider: Postal:
20th Street and Constitution Avenue, NW, Washington, DC 20551

Web page: http://www.federalreserve.gov/

More information through EDIRC

Order Information: Web: http://www.federalreserve.gov/pubs/feds/fedsorder.html

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. M. Hashem Pesaran, 2004. "General Diagnostic Tests for Cross Section Dependence in Panels," CESifo Working Paper Series 1229, CESifo Group Munich.
  2. Rodrigo Alfaro & Mathias Drehmann, 2009. "Macro stress tests and crises: what can we learn?," BIS Quarterly Review, Bank for International Settlements, December.
  3. Jonah B. Gelbach & Doug Miller, 2009. "Robust Inference with Multi-way Clustering," Working Papers 99, University of California, Davis, Department of Economics.
  4. William B. English & Skander J. van den Heuvel & Egon Zakrajsek, 2012. "Interest rate risk and bank equity valuations," Finance and Economics Discussion Series 2012-26, Board of Governors of the Federal Reserve System (U.S.).
  5. 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.
  6. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
  7. 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.
  8. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2010. "Quantile and Probability Curves without Crossing," Post-Print hal-01052958, HAL.
  9. Roger Koenker & Zhijie Xiao, 2002. "Inference on the Quantile Regression Process," Econometrica, Econometric Society, vol. 70(4), pages 1583-1612, July.
  10. Marcella Lucchetta & Gianni De Nicolo, 2012. "Systemic Real and Financial Risks; Measurement, Forecasting, and Stress Testing," IMF Working Papers 12/58, International Monetary Fund.
  11. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-26, November.
  12. Martin Cihak, 2007. "Introduction to Applied Stress Testing," IMF Working Papers 07/59, International Monetary Fund.
  13. Lamarche, Carlos, 2010. "Robust penalized quantile regression estimation for panel data," Journal of Econometrics, Elsevier, vol. 157(2), pages 396-408, August.
  14. Ricardo Schechtman & Wagner Piazza Gaglianone, 2011. "Macro Stress Testing of Credit Risk Focused on the Tails," Working Papers Series 241, Central Bank of Brazil, Research Department.
  15. Boivin, Jean & Giannoni, Marc & Stevanovic, Dalibor, 2013. "Dynamic effects of credit shocks in a data-rich environment," Staff Reports 615, Federal Reserve Bank of New York, revised 01 Oct 2016.
  16. 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.
  17. Simon Gilchrist & Egon Zakrajšek, 2011. "Credit Spreads and Business Cycle Fluctuations," NBER Working Papers 17021, National Bureau of Economic Research, Inc.
  18. Beverly Hirtle & Til Schuermann & Kevin J. Stiroh, 2009. "Macroprudential supervision of financial institutions: lessons from the SCAP," Staff Reports 409, Federal Reserve Bank of New York.
  19. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2011. "Robust Inference With Multiway Clustering," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 238-249, April.
  20. González-Rivera, Gloria & Yoldas, Emre, 2012. "Autocontour-based evaluation of multivariate predictive densities," International Journal of Forecasting, Elsevier, vol. 28(2), pages 328-342.
  21. Samuel G. Hanson & Anil K. Kashyap & Jeremy C. Stein, 2011. "A Macroprudential Approach to Financial Regulation," Journal of Economic Perspectives, American Economic Association, vol. 25(1), pages 3-28, Winter.
  22. Jon Faust & Simon Gilchrist & Jonathan H. Wright & Egon Zakrajšsek, 2013. "Credit Spreads as Predictors of Real-Time Economic Activity: A Bayesian Model-Averaging Approach," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1501-1519, December.
  23. repec:spo:wpecon:info:hdl:2441/5rkqqmvrn4tl22s9mc4b6ga2g is not listed on IDEAS
  24. Anthony Tay & Kenneth F. Wallis, 2000. "Density Forecasting: A Survey," Econometric Society World Congress 2000 Contributed Papers 0370, Econometric Society.
  25. 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.
  26. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
  27. Koenker, Roger & Xiao, Zhijie, 2006. "Quantile Autoregression," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 980-990, September.
  28. Marco Sorge, 2004. "Stress-testing financial systems: an overview of current methodologies," BIS Working Papers 165, Bank for International Settlements.
  29. Donald P. Morgan & Stavros Peristiani & Vanessa Savino, 2010. "The information value of the stress test and bank opacity," Staff Reports 460, Federal Reserve Bank of New York.
  30. Luca Guerrieri & Michelle Welch, 2012. "Can macro variables used in stress testing forecast the performance of banks?," Finance and Economics Discussion Series 2012-49, Board of Governors of the Federal Reserve System (U.S.).
  31. Koenker, Roger, 2004. "Quantile regression for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 74-89, October.
  32. 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.
  33. 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.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:fip:fedgfe:2013-55. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Franz Osorio)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.