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Scenario-based stress tests: are they painful enough?

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  • Colin Ellis

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  • Colin Ellis, 2017. "Scenario-based stress tests: are they painful enough?," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 11(2), June.
    • Handle: RePEc:wyz:journl:id:502
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    1. Glenn Hoggarth & Steffen Sorensen & Lea Zicchino, 2005. "Stress tests of UK banks using a VAR approach," Bank of England working papers 282, Bank of England.
    2. Peter Grundke & Kamil Pliszka, 2018. "A macroeconomic reverse stress test," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 1093-1130, May.
    3. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    4. Jeremy Berkowitz, 1999. "A coherent framework for stress-testing," Finance and Economics Discussion Series 1999-29, Board of Governors of the Federal Reserve System (U.S.).
    5. Colin Ellis, 2006. "Elasticities, markups and technical progress: evidence from a state-space approach," Bank of England working papers 300, Bank of England.
    6. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
    7. Borio, Claudio & Drehmann, Mathias & Tsatsaronis, Kostas, 2014. "Stress-testing macro stress testing: Does it live up to expectations?," Journal of Financial Stability, Elsevier, vol. 12(C), pages 3-15.
    8. Gordy, Michael B., 2003. "A risk-factor model foundation for ratings-based bank capital rules," Journal of Financial Intermediation, Elsevier, vol. 12(3), pages 199-232, July.
    9. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(1), pages 387-422.
    10. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    11. Azamat Abdymomunov & Sharon Blei & Bakhodir Ergashev, 2015. "Integrating Stress Scenarios into Risk Quantification Models," Journal of Financial Services Research, Springer;Western Finance Association, vol. 47(1), pages 57-79, February.
    12. Donald Coletti & Benjamin Hunt & David Rose & Robert Tetlow, 1996. "The Bank of Canada's New Quarterly Projection Model. Part 3 , the Dynamic Model : QPM," Technical Reports 75, Bank of Canada.
    13. Kenneth F. Wallis, 2004. "An Assessment of Bank of England and National Institute Inflation Forecast Uncertainties," National Institute Economic Review, National Institute of Economic and Social Research, vol. 189(1), pages 64-71, July.
    14. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    15. Olivier Jean Blanchard & Stanley Fischer, 1989. "Lectures on Macroeconomics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262022834, December.
    16. Nigel Pain & Christine Lewis & Thai-Thanh Dang & Yosuke Jin & Pete Richardson, 2014. "OECD Forecasts During and After the Financial Crisis: A Post Mortem," OECD Economics Department Working Papers 1107, OECD Publishing.
    17. Darren Flood & Philip Lowe, 1995. "Inventories and the Business Cycle," The Economic Record, The Economic Society of Australia, vol. 71(1), pages 27-39, March.
    18. McNeil, Alexander J. & Smith, Andrew D., 2012. "Multivariate stress scenarios and solvency," Insurance: Mathematics and Economics, Elsevier, vol. 50(3), pages 299-308.
    19. Christine Lewis & Nigel Pain, 2014. "Lessons from OECD forecasts during and after the financial crisis," OECD Journal: Economic Studies, OECD Publishing, vol. 2014(1), pages 9-39.
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