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An Early-warning and Dynamic Forecasting Framework of Default Probabilities for the Macroprudential Policy Indicators Arsenal

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  • Xisong Jin

    ()

  • Francisco Nadal De Simone

    ()

Abstract

The estimation of banks? marginal probabilities of default using structural credit risk models can be enriched incorporating macro-financial variables readily available to economic agents. By combining Delianedis and Geske?s model with a Generalized Dynamic Factor Model into a dynamic t-copula as a mechanism for obtaining banks? dependence, this paper develops a framework that generates an early warning indicator and robust out-of-sample forecasts of banks? probabilities of default. The database comprises both a set of Luxembourg banks and the European banking groups to which they belong. The main results of this study are, first, that the common component of the forward probability of banks? defaulting on their long-term debt, conditional on not defaulting on their short-term debt, contains a significant early warning feature of interest for an operational macroprudential framework driven by economic activity, credit and interbank activity. Second, incorporating the common and the idiosyncratic components of macro-financial variables improves the analytical features and the out-of-sample forecasting performance of the framework proposed.

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File URL: http://www.bcl.lu/fr/publications/cahiers_etudes/75/BCLWP075.pdf
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Bibliographic Info

Paper provided by Central Bank of Luxembourg in its series BCL working papers with number 75.

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Length: 45 pages
Date of creation: Jul 2012
Date of revision:
Handle: RePEc:bcl:bclwop:bclwp075

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Web page: http://www.bcl.lu/

Related research

Keywords: financial stability; macroprudential policy; credit risk; early warning indicators; default probability; Generalized Dynamic Factor Model; dynamic copulas; GARCH;

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References

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  1. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2002. "Do Financial Variables Help Forecasting Inflation and Real Activity in the Euro Area?," CEPR Discussion Papers 3146, C.E.P.R. Discussion Papers.
  2. Alessi, Lucia & Barigozzi, Matteo & Capasso, Marco, 2008. "A robust criterion for determining the number of static factors in approximate factor models," Working Paper Series 0903, European Central Bank.
  3. Marcos Souto & Benjamin M. Tabak & Francisco Vazquez, 2009. "Linking Financial and Macroeconomic Factors to Credit Risk Indicators of Brazilian Banks," Working Papers Series 189, Central Bank of Brazil, Research Department.
  4. Thorsten Lehnert & Xisong Jin & Francisco Nadal de Simone, 2011. "Does the GARCH Structural Credit Risk Model Make a Difference?," LSF Research Working Paper Series 11-6, Luxembourg School of Finance, University of Luxembourg.
  5. Dean Fantazzini, 2008. "Dynamic Copula Modelling for Value at Risk," Frontiers in Finance and Economics, SKEMA Business School, vol. 5(2), pages 72-108, October.
  6. D'Agostino, Antonello & McQuinn, Kieran & O'Brien, Derry, 2008. "Now-casting Irish GDP," Research Technical Papers 9/RT/08, Central Bank of Ireland.
  7. Monica Billio & Mila Getmansky & Andrew W. Lo & Loriana Pelizzon, 2010. "Econometric Measures of Systemic Risk in the Finance and Insurance Sectors," NBER Working Papers 16223, National Bureau of Economic Research, Inc.
  8. Siem Jan Koopman & Andre Lucas & Bernd Schwaab, 2010. "Macro, Industry and Frailty Effects in Defaults: The 2008 Credit Crisis in Perspective," Tinbergen Institute Discussion Papers 10-004/2, Tinbergen Institute, revised 24 Aug 2010.
  9. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2006. "Dynamic Factor GARCH: Multivariate Volatility Forecast for a Large Number of Series," LEM Papers Series 2006/25, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  10. Xisong Jin & Francisco Nadal de Simone, 2011. "Market- and Book-Based Models of Probability of Default for Developing Macroprudential Policy Tools," BCL working papers 65, Central Bank of Luxembourg.
  11. Jeffrey A. Frankel & George Saravelos, 2010. "Are Leading Indicators of Financial Crises Useful for Assessing Country Vulnerability? Evidence from the 2008-09 Global Crisis," NBER Working Papers 16047, National Bureau of Economic Research, Inc.
  12. Bernd Schwaab & Andre Lucas & Siem Jan Koopman, 2010. "Systemic Risk Diagnostics," Tinbergen Institute Discussion Papers 10-104/2/DSF 2, Tinbergen Institute, revised 29 Nov 2010.
  13. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2006. "Generalized Dynamic Factor Model + GARCH Exploiting Multivariate Information for Univariate Prediction," LEM Papers Series 2006/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
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Cited by:
  1. Xisong Jin & Francisco Nadal De Simone, 2013. "Banking Systemic Vulnerabilities: A Tail-risk Dynamic CIMDO Approach," BCL working papers 82, Central Bank of Luxembourg.

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