Analysis of default data using hidden Markov models
AbstractThe occurrence of defaults within a bond portfolio is modelled as a simple hidden Markov process. The hidden variable represents the risk state, which is assumed to be common to all bonds within one particular sector and region. After describing the model and recalling the basic properties of hidden Markov chains, we show how to apply the model to a simulated sequence of default events. Then, we consider a real scenario, with default events taken from a large database provided by Standard & Poor's. We are able to obtain estimates for the model parameters and also to reconstruct the most likely sequence of the risk state. Finally, we address the issue of global versus industry-specific risk factors. By extending our model to include independent hidden risk sequences, we can disentangle the risk associated with the business cycle from that specific to the individual sector.
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 InfoArticle provided by Taylor & Francis Journals in its journal Quantitative Finance.
Volume (Year): 5 (2005)
Issue (Month): 1 ()
Contact details of provider:
Web page: http://www.tandfonline.com/RQUF20
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Bruche, Max & González-Aguado, Carlos, 2010.
"Recovery rates, default probabilities, and the credit cycle,"
Journal of Banking & Finance,
Elsevier, vol. 34(4), pages 754-764, April.
- Max Bruche & Carlos Gonzalez-Aguado, 2006. "Recovery rates, default probabilities and the credit cycle," LSE Research Online Documents on Economics 24524, London School of Economics and Political Science, LSE Library.
- Max Bruche & Carlos González Aguado, 2006. "Recovery Rates, Default Probabilities And The Credit Cycle," Working Papers wp2006_0612, CEMFI.
- Carlos González-Aguado & Max Bruche, 2006. "Recovery Rates, Default Probabilities and the Credit Cycle," FMG Discussion Papers dp572, Financial Markets Group.
- Sigmund, Michael & Kerbl, Stefan, 2011. "What Drives Aggregate Credit Risk?," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 22.
- Xing, Haipeng & Sun, Ning & Chen, Ying, 2012. "Credit rating dynamics in the presence of unknown structural breaks," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 78-89.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If references are entirely missing, you can add them using this form.