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

Systemic Risk Diagnostics

Listed author(s):
  • Bernd Schwaab

    ()

    (VU University Amsterdam, and European Central Bank)

  • Andre Lucas

    ()

    (VU University Amsterdam)

  • Siem Jan Koopman

    ()

    (VU University Amsterdam)

A macro-prudential policy maker can manage risks to financial stability only if currentand future risks can be reliably assessed. We propose a novel framework to assessfinancial system risk. Using a dynamic factor framework based on state-space methods, we model latent macro-financial and credit risk components for a large data setcomprising the U.S., the EU-27 area, and the rest of the world. Controlling for global,region-specific, and industry effects, we construct coincident measures ('thermometers')and forward looking indicators of financial distress and the likelihood of financial melt-down. We find that credit risk conditions can significantly and persistently de-couplefrom macro-financial fundamentals. Such decoupling can serve as an early warningsignal for macro-prudential policy.

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://papers.tinbergen.nl/10104.pdf
Download Restriction: no

Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 10-104/2/DSF 2.

as
in new window

Length:
Date of creation: 18 Oct 2010
Date of revision: 29 Nov 2010
Handle: RePEc:tin:wpaper:20100104
Contact details of provider: Postal:
Gustav Mahlerplein 117, 1082 MS Amsterdam

Phone: +31 (0)20 598 4580
Web page: http://www.tinbergen.nl/
Email:


More information through EDIRC

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. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
  2. Dilip Abreu & Markus K. Brunnermeier, 2003. "Bubbles and Crashes," Econometrica, Econometric Society, vol. 71(1), pages 173-204, January.
  3. Darrell Duffie & Andreas Eckner & Guillaume Horel & Leandro Saita, 2009. "Frailty Correlated Default," Journal of Finance, American Finance Association, vol. 64(5), pages 2089-2123, October.
  4. Philipp Hartmann & Stefan Straetmans & Casper de Vries, 2007. "Banking System Stability. A Cross-Atlantic Perspective," NBER Chapters,in: The Risks of Financial Institutions, pages 133-192 National Bureau of Economic Research, Inc.
  5. David Aikman & Piergiorgio Alessandri & Bruno Eklund & Prasanna Gai & Sujit Kapadia & Elizabeth Martin & Nada Mora & Gabriel Sterne & Matthew Willison, 2011. "Funding Liquidity Risk in a Quantitative Model of Systemic Stability," Central Banking, Analysis, and Economic Policies Book Series,in: Rodrigo Alfaro (ed.), Financial Stability, Monetary Policy, and Central Banking, edition 1, volume 15, chapter 12, pages 371-410 Central Bank of Chile.
  6. Charles Goodhart & Pojanart Sunirand & Dimitrios Tsomocos, 2006. "A model to analyse financial fragility," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 27(1), pages 107-142, January.
  7. Koopman, Siem Jan & Lucas, Andre & Monteiro, Andre, 2008. "The multi-state latent factor intensity model for credit rating transitions," Journal of Econometrics, Elsevier, vol. 142(1), pages 399-424, January.
  8. Koopman, Siem Jan & Lucas, André, 2008. "A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 510-525.
  9. Huang, Xin & Zhou, Hao & Zhu, Haibin, 2009. "A framework for assessing the systemic risk of major financial institutions," Journal of Banking & Finance, Elsevier, vol. 33(11), pages 2036-2049, November.
  10. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
  11. Hartmann, Philipp & Straetmans, Stefan & de Vries, Casper, 2005. "Banking system stability: a cross-Atlantic perspective," Working Paper Series 527, European Central Bank.
  12. McNeil, Alexander J. & Wendin, Jonathan P., 2007. "Bayesian inference for generalized linear mixed models of portfolio credit risk," Journal of Empirical Finance, Elsevier, vol. 14(2), pages 131-149, March.
  13. Markus K. Brunnermeier, 2009. "Deciphering the Liquidity and Credit Crunch 2007-2008," Journal of Economic Perspectives, American Economic Association, vol. 23(1), pages 77-100, Winter.
  14. J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, vol. 89(3), pages 603-616, August.
  15. Sanjiv R. Das & Darrell Duffie & Nikunj Kapadia & Leandro Saita, 2007. "Common Failings: How Corporate Defaults Are Correlated," Journal of Finance, American Finance Association, vol. 62(1), pages 93-117, February.
  16. Angela Maddaloni & Jose-Luis Peydro, 2011. "Bank Risk-taking, Securitization, Supervision, and Low Interest Rates: Evidence from the Euro-area and the U.S. Lending Standards," Review of Financial Studies, Society for Financial Studies, vol. 24(6), pages 2121-2165.
  17. Barrell, Ray & Davis, E. Philip & Karim, Dilruba & Liadze, Iana, 2010. "Bank regulation, property prices and early warning systems for banking crises in OECD countries," Journal of Banking & Finance, Elsevier, vol. 34(9), pages 2255-2264, September.
  18. Monica Billio & Mila Getmansky & Andrew W. Lo & Loriana Pelizzon, 2010. "Econometric Measures of Systemic Risk in the Finance and Insurance Sectors," NBER Chapters,in: Market Institutions and Financial Market Risk National Bureau of Economic Research, Inc.
  19. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
  20. Miroslav Misina & Greg Tkacz, 2008. "Credit, Asset Prices, and Financial Stress in Canada," Staff Working Papers 08-10, Bank of Canada.
  21. Siem Jan Koopman & André Lucas & Bernd Schwaab, 2008. "Forecasting Cross-Sections of Frailty-Correlated Default," Tinbergen Institute Discussion Papers 08-029/4, Tinbergen Institute.
  22. Philip Lowe & Claudio Borio, 2002. "Asset prices, financial and monetary stability: exploring the nexus," BIS Working Papers 114, Bank for International Settlements.
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:tin:wpaper:20100104. 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: (Tinbergen Office +31 (0)10-4088900)

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.