Can macro variables used in stress testing forecast the performance of banks?
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References listed on IDEAS
- Quagliariello,Mario (ed.), 2009. "Stress-testing the Banking System," Cambridge Books, Cambridge University Press, number 9780521767309, September.
- Clark, Todd E. & West, Kenneth D., 2007.
"Approximately normal tests for equal predictive accuracy in nested models,"
Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
- Todd E. Clark & Kenneth D. West, 2005. "Approximately normal tests for equal predictive accuracy in nested models," Research Working Paper RWP 05-05, Federal Reserve Bank of Kansas City.
- Kenneth D. West & Todd Clark, 2006. "Approximately Normal Tests for Equal Predictive Accuracy in Nested Models," NBER Technical Working Papers 0326, National Bureau of Economic Research, Inc.
- Estrella, Arturo & Hardouvelis, Gikas A, 1991.
"The Term Structure as a Predictor of Real Economic Activity,"
Journal of Finance, American Finance Association, vol. 46(2), pages 555-576, June.
- Arturo Estrella & Gikas A. Hardouvelis, 1989. "The term structure as a predictor of real economic activity," Research Paper 8907, Federal Reserve Bank of New York.
- Crook, Jonathan & Banasik, John, 2012. "Forecasting and explaining aggregate consumer credit delinquency behaviour," International Journal of Forecasting, Elsevier, vol. 28(1), pages 145-160.
- Maria Soledad Martinez Peria & Mr. Giovanni Majnoni & Mr. Matthew T Jones & Mr. Winfrid Blaschke, 2001. "Stress Testing of Financial Systems: An Overview of Issues, Methodologies, and FSAP Experiences," IMF Working Papers 2001/088, International Monetary Fund.
- Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
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Cited by:
- Acharya, Viral V. & Berger, Allen N. & Roman, Raluca A., 2018. "Lending implications of U.S. bank stress tests: Costs or benefits?," Journal of Financial Intermediation, Elsevier, vol. 34(C), pages 58-90.
- Wu, Deming & Fang, Ming & Wang, Qing, 2018. "An empirical study of bank stress testing for auto loans," Journal of Financial Stability, Elsevier, vol. 39(C), pages 79-89.
- Kolari, James W. & López-Iturriaga, Félix J. & Sanz, Ivan Pastor, 2019. "Predicting European bank stress tests: Survival of the fittest," Global Finance Journal, Elsevier, vol. 39(C), pages 44-57.
- Covas, Francisco B. & Rump, Ben & Zakrajšek, Egon, 2014.
"Stress-testing US bank holding companies: A dynamic panel quantile regression approach,"
International Journal of Forecasting, Elsevier, vol. 30(3), pages 691-713.
- Francisco Covas & Ben Rump & Egon Zakrajšek, 2013. "Stress-testing U.S. bank holding companies: a dynamic panel quantile regression approach," Finance and Economics Discussion Series 2013-55, Board of Governors of the Federal Reserve System (U.S.).
- repec:aei:rpaper:008586461 is not listed on IDEAS
- Brummelhuis, Raymond & Luo, Zhongmin, 2019. "Bank Net Interest Margin Forecasting and Capital Adequacy Stress Testing by Machine Learning Techniques," MPRA Paper 94779, University Library of Munich, Germany.
- Pritsker, Matt, 2019. "An overview of regulatory stress-testing and steps to improve it," Global Finance Journal, Elsevier, vol. 39(C), pages 39-43.
- Fang, Cao & Yeager, Timothy J., 2020. "A historical loss approach to community bank stress testing," Journal of Banking & Finance, Elsevier, vol. 118(C).
- Hirtle, Beverly & Kovner, Anna & Vickery, James & Bhanot, Meru, 2016.
"Assessing financial stability: The Capital and Loss Assessment under Stress Scenarios (CLASS) model,"
Journal of Banking & Finance, Elsevier, vol. 69(S1), pages 35-55.
- Meru Bhanot & Beverly Hirtle & Anna Kovner & James Vickery, 2014. "Assessing financial stability: the Capital and Loss Assessment under Stress Scenarios (CLASS) model," Staff Reports 663, Federal Reserve Bank of New York.
- Matthew Pritsker, 2017. "Choosing Stress Scenarios for Systemic Risk Through Dimension Reduction," Supervisory Research and Analysis Working Papers RPA 17-4, Federal Reserve Bank of Boston.
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NEP fields
This paper has been announced in the following NEP Reports:- NEP-BAN-2012-09-16 (Banking)
- NEP-FOR-2012-09-16 (Forecasting)
- NEP-MAC-2012-09-16 (Macroeconomics)
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