An Early-warning and Dynamic Forecasting Framework of Default Probabilities for the Macroprudential Policy Indicators Arsenal
AbstractThe 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.
Download InfoIf 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.
Bibliographic InfoPaper provided by Central Bank of Luxembourg in its series BCL working papers with number 75.
Length: 45 pages
Date of creation: Jul 2012
Date of revision:
Contact details of provider:
Web page: http://www.bcl.lu/
financial stability; macroprudential policy; credit risk; early warning indicators; default probability; Generalized Dynamic Factor Model; dynamic copulas; GARCH;
Find related papers by JEL classification:
- C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
- E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
- G1 - Financial Economics - - General Financial Markets
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-09-09 (All new papers)
- NEP-BAN-2012-09-09 (Banking)
- NEP-CBA-2012-09-09 (Central Banking)
- NEP-ECM-2012-09-09 (Econometrics)
- NEP-FOR-2012-09-09 (Forecasting)
- NEP-RMG-2012-09-09 (Risk Management)
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.:
- 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.
- 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.
- 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.
- Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2007. "A Robust Criterion for Determining the Number of Static Factors in Approximate Factor Models," LEM Papers Series 2007/19, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
- Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2003.
"Do financial variables help forecasting inflation and real activity in the euro area?,"
Journal of Monetary Economics,
Elsevier, vol. 50(6), pages 1243-1255, September.
- Marc Hallin & Mario Forni & Marco Lippi & Lucrezia Reichlin, 2003. "Do financial variables help forecasting inflation and real activity in the Euro area ?," ULB Institutional Repository 2013/2123, ULB -- Universite Libre de Bruxelles.
- 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.
- 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.
- Antonello D'Agostino & Kieran McQuinn & Derry O’Brien, 2012.
"Nowcasting Irish GDP,"
OECD Journal: Journal of Business Cycle Measurement and Analysis,
OECD Publishing,CIRET, vol. 2012(2), pages 21-31.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- Xisong Jin & Francisco Nadal De Simone, 2013. "Banking Systemic Vulnerabilities: A Tail-risk Dynamic CIMDO Approach," BCL working papers 82, Central Bank of Luxembourg.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ().
If references are entirely missing, you can add them using this form.