Modelling Portfolio Defaults Using Hidden Markov Models with Covariates
We extend the hidden Markov Model for defaults of Crowder et al. (2005, Quantitative Finance 5, 27--34) to include covariates. The covariates enhance the prediction of transition probabilities from high to low default regimes. To estimate the model, we extend the EM estimating equations to account for the time varying nature of the conditional likelihoods due to sample attrition and extension. Using empirical U.S. default data, we find that GDP growth, the term structure of interest rates and stock market returns impact the state transition probabilities. The impact, however, is not uniform across industries. We only find a weak correspondence between industry credit cycle dynamics and general business cycles. Copyright Royal Economic Society 2008
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Volume (Year): 11 (2008)
Issue (Month): 1 (03)
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- Koopman, Siem Jan & Kräussl, Roman & Lucas, André & Monteiro, André B., 2009.
"Credit cycles and macro fundamentals,"
Journal of Empirical Finance,
Elsevier, vol. 16(1), pages 42-54, January.
- Koopman, Siem Jan & Kräussl, Roman & Lucas, André, 2006. "Credit cycles and macro fundamentals," CFS Working Paper Series 2006/33, Center for Financial Studies (CFS).
- Siem Jan Koopman & Roman Kraeussl & Andre Lucas & Andre Monteiro, 2006. "Credit Cycles and Macro Fundamentals," Tinbergen Institute Discussion Papers 06-023/2, Tinbergen Institute.
- Anil Bangia & Francis X. Diebold & Til Schuermann, 2000.
"Ratings Migration and the Business Cycle, With Application to Credit Portfolio Stress Testing,"
Center for Financial Institutions Working Papers
00-26, Wharton School Center for Financial Institutions, University of Pennsylvania.
- Bangia, Anil & Diebold, Francis X. & Kronimus, Andre & Schagen, Christian & Schuermann, Til, 2002. "Ratings migration and the business cycle, with application to credit portfolio stress testing," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 445-474, March.
- Darrell Duffie & Leandro Siata & Ke Wang, 2006.
"Multi-Period Corporate Default Prediction With Stochastic Covariates,"
NBER Working Papers
11962, National Bureau of Economic Research, Inc.
- Duffie, Darrell & Saita, Leandro & Wang, Ke, 2007. "Multi-period corporate default prediction with stochastic covariates," Journal of Financial Economics, Elsevier, vol. 83(3), pages 635-665, March.
- Darrel Duffie & Leandro Saita & Ke Wang, 2005. "Multi-Period Corporate Default Prediction With Stochastic Covariates," CIRJE F-Series CIRJE-F-373, CIRJE, Faculty of Economics, University of Tokyo.
- Darrel Duffie & Leandro Saita & Ke Wang, 2005. "Multi-Period Corporate Default Prediction With Stochastic Covariates," CARF F-Series CARF-F-047, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
- Pamela Nickell & William Perraudin & Simone Varotto, 2001.
"Stability of ratings transitions,"
Bank of England working papers
133, Bank of England.
- Lucas, Andre & Klaassen, Pieter, 2006.
"Discrete versus continuous state switching models for portfolio credit risk,"
Journal of Banking & Finance,
Elsevier, vol. 30(1), pages 23-35, January.
- André Lucas & Pieter Klaassen, 2003. "Discrete versus Continuous State Switching Models for Portfolio Credit Risk," Tinbergen Institute Discussion Papers 03-075/2, Tinbergen Institute, revised 30 Sep 2003.
- Koopman, Siem Jan & Lucas, AndrÃ©, 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.
- Siem Jan Koopman & André Lucas & Robert J. Daniels, 2005. "A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk," DNB Working Papers 055, Netherlands Central Bank, Research Department.
- Siem Jan Koopman & André Lucas & Robert Daniels, 2005. "A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk," Tinbergen Institute Discussion Papers 05-060/4, Tinbergen Institute.
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