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Evaluating the Information Value for Measures of Systemic Conditions

Author

Listed:
  • John Dooley
  • Dieter Gramlich
  • Mikhail V. Oet
  • Stephen J. Ong
  • Peter Sarlin

Abstract

Timely identification of coincident systemic conditions and forward-looking capacity to anticipate adverse developments are critical for macroprudential policy. Despite clear recognition of these factors in literature, an evaluation methodology and empirical tests for the information value of coincident measures are lacking. This paper provides a twofold contribution to the literature: (i) a general-purpose evaluation framework for assessing information value for measures of systemic conditions, and (ii) an empirical assessment of the information value for several alternative measures of US systemic conditions. We find substantial differences among the measures, of which the Cleveland Financial Stress Index shows best-in-class identification performance. In terms of forecasting performance, Kamakura?s Troubled Company Index, Cleveland Financial Stress Index, and Goldman Sachs Financial Conditions Index show moderately stable usefulness metrics over time.

Suggested Citation

  • John Dooley & Dieter Gramlich & Mikhail V. Oet & Stephen J. Ong & Peter Sarlin, 2015. "Evaluating the Information Value for Measures of Systemic Conditions," Working Papers (Old Series) 1513, Federal Reserve Bank of Cleveland.
    • Handle: RePEc:fip:fedcwp:1513
    DOI: 10.26509/frbc-wp-201513
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    References listed on IDEAS

    as
    1. C. H. Hommes, 2001. "Financial markets as nonlinear adaptive evolutionary systems," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 149-167.
    2. Luc Laeven & Fabian Valencia, 2020. "Systemic Banking Crises Database II," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 68(2), pages 307-361, June.
    3. Babecký, Jan & Havránek, Tomáš & Matějů, Jakub & Rusnák, Marek & Šmídková, Kateřina & Vašíček, Bořek, 2013. "Leading indicators of crisis incidence: Evidence from developed countries," Journal of International Money and Finance, Elsevier, vol. 35(C), pages 1-19.
    4. A. Joanne Kellermann & Jakob de Haan & Femke de Vries (ed.), 2013. "Financial Supervision in the 21st Century," Springer Books, Springer, edition 127, number 978-3-642-36733-5, December.
    5. Alessi, Lucia & Detken, Carsten, 2011. "Quasi real time early warning indicators for costly asset price boom/bust cycles: A role for global liquidity," European Journal of Political Economy, Elsevier, vol. 27(3), pages 520-533, September.
    6. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    7. Hali J. Edison, 2003. "Do indicators of financial crises work? An evaluation of an early warning system," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 8(1), pages 11-53.
    8. Graciela Kaminsky & Saul Lizondo & Carmen M. Reinhart, 1998. "Leading Indicators of Currency Crises," IMF Staff Papers, Palgrave Macmillan, vol. 45(1), pages 1-48, March.
    9. Kevin L. Kliesen & Michael T. Owyang & E. Katarina Vermann, 2012. "Disentangling diverse measures: a survey of financial stress indexes," Review, Federal Reserve Bank of St. Louis, issue Sep, pages 369-398.
    10. Davis, E. Philip & Karim, Dilruba, 2008. "Comparing early warning systems for banking crises," Journal of Financial Stability, Elsevier, vol. 4(2), pages 89-120, June.
    11. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    12. Markus Holopainen & Peter Sarlin, 2015. "Toward robust early-warning models: A horse race, ensembles and model uncertainty," Papers 1501.04682, arXiv.org, revised Apr 2016.
    13. Betz, Frank & Oprică, Silviu & Peltonen, Tuomas A. & Sarlin, Peter, 2014. "Predicting distress in European banks," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 225-241.
    14. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    15. Sharada Alampalli, 2013. "Information infrastructure for systemic regulation," Journal of Financial Regulation and Compliance, Emerald Group Publishing Limited, vol. 21(3), pages 204-216, July.
    16. Oet, Mikhail V. & Bianco, Timothy & Gramlich, Dieter & Ong, Stephen J., 2013. "SAFE: An early warning system for systemic banking risk," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4510-4533.
    17. Alex Cukierman, 2011. "Reflections on the Crisis and on its Lessons for Regulatory Reforms and for Central Bank Policies," Chapters, in: Sylvester Eijffinger & Donato Masciandaro (ed.), Handbook of Central Banking, Financial Regulation and Supervision, chapter 3, Edward Elgar Publishing.
    18. repec:zbw:bofrdp:2015_006 is not listed on IDEAS
    19. Fuertes, Ana-Maria & Kalotychou, Elena, 2007. "Optimal design of early warning systems for sovereign debt crises," International Journal of Forecasting, Elsevier, vol. 23(1), pages 85-100.
    20. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    21. Claudio Borio, 2003. "Towards a Macroprudential Framework for Financial Supervision and Regulation?," CESifo Economic Studies, CESifo Group, vol. 49(2), pages 181-215.
    22. repec:cnb:ocpubc:fsr1011/1 is not listed on IDEAS
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    Cited by:

    1. Mikhail V. Oet & John M. Dooley & Stephen J. Ong, 2015. "The Financial Stress Index: Identification of Systemic Risk Conditions," Risks, MDPI, vol. 3(3), pages 1-25, September.
    2. Mikhail V. Oet & John M. Dooley & Amanda C. Janosko & Dieter Gramlich & Stephen J. Ong, 2015. "Supervising System Stress in Multiple Markets," Risks, MDPI, vol. 3(3), pages 1-25, September.

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    More about this item

    Keywords

    Information value; Systemic conditions; Coincident measures; Early warning; Macroprudential policy;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • G01 - Financial Economics - - General - - - Financial Crises
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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