The multi-state latent factor intensity model for credit rating transitions
A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic factors. The model has a generalized semi-Markov structure designed to accommodate many of the stylized facts of credit rating migrations. Parameter estimation is based on Monte Carlo maximum likelihood methods for which the details are discussed in this paper. A simulation experiment is carried out to show the effectiveness of the estimation procedure. An empirical application is presented for transitions in a 7 grade rating system. The model includes a common dynamic component that can be interpreted as the credit cycle. Asymmetric effects of this cycle across rating grades and additional semi-Markov dynamics are found to be statistically significant. Finally, we investigate whether the common factor model suffices to capture systematic risk in rating transition data by introducing multiple factors in the model. This discussion paper has resulted in a publication in the Journal of Econometrics , 142(1), 399-424.
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- Van den Berg, Gerard J., 2001.
"Duration models: specification, identification and multiple durations,"
Handbook of Econometrics,
in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 55, pages 3381-3460
- Van den Berg, Gerard J., 2000. "Duration Models: Specification, Identification, and Multiple Durations," MPRA Paper 9446, University Library of Munich, Germany.
- BAUWENS, Luc & HAUTSCH, Nikolaus, 2003. "Dynamic latent factor models for intensity processes," CORE Discussion Papers 2003103, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Koopman, Siem Jan & Kräussl, Roman & Lucas, André, 2006.
"Credit cycles and macro fundamentals,"
CFS Working Paper Series
2006/33, Center for Financial Studies (CFS).
- 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," CARF F-Series CARF-F-047, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
- 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.
- Durbin, James & Koopman, Siem Jan, 2001.
"Time Series Analysis by State Space Methods,"
Oxford University Press, number 9780198523543, July.
- Tom Doan, . "SEASONALDLM: RATS procedure to create the matrices for the seasonal component of a DLM," Statistical Software Components RTS00251, Boston College Department of Economics.
- Siem Jan Koopman & Andr� 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.
- 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 & Andr� 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.
- Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
- Siem Jan Koopman & Andr� Lucas, 2003.
"Business and Default Cycles for Credit Risk,"
Tinbergen Institute Discussion Papers
03-062/2, Tinbergen Institute, revised 09 Jan 2003.
- 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.
- 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.
- Siem Jan Koopman & Neil Shephard & Jurgen A. Doornik, 1999.
"Statistical algorithms for models in state space using SsfPack 2.2,"
Royal Economic Society, vol. 2(1), pages 107-160.
- Neil Shephard & Jurgen Doornik & Siem Jan Koopman, 1998. "Statistical algorithms for models in state space using SsfPack 2.2," Economics Series Working Papers 1998-W06, University of Oxford, Department of Economics.
- Koopman, S.J.M. & Shephard, N. & Doornik, J.A., 1998. "Statistical Algorithms for Models in State Space Using SsfPack 2.2," Discussion Paper 1998-141, Tilburg University, Center for Economic Research.
- Gagliardini, P. & Gourieroux, C., 2005. "Migration correlation: Definition and efficient estimation," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 865-894, April.
- Carling, Kenneth & Jacobson, Tor & Lindé, Jesper & Roszbach, Kasper, 2002. "Capital Charges under Basel II: Corporate Credit Risk Modelling and the Macro Economy," Working Paper Series 142, Sveriges Riksbank (Central Bank of Sweden).
- Koopman, Siem Jan & Lucas, Andre & Klaassen, Pieter, 2005. "Empirical credit cycles and capital buffer formation," Journal of Banking & Finance, Elsevier, vol. 29(12), pages 3159-3179, December.
- Liesenfeld, Roman & Richard, Jean-Francois, 2003. "Univariate and multivariate stochastic volatility models: estimation and diagnostics," Journal of Empirical Finance, Elsevier, vol. 10(4), pages 505-531, September.
- Patrick Gagliardini & Christian Gourieroux, 2004.
"Stochastic Migration Models with Application to Corporate Risk,"
2004-35, Centre de Recherche en Economie et Statistique.
- Patrick Gagliardini, 2005. "Stochastic Migration Models with Application to Corporate Risk," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 3(2), pages 188-226.
- Lando, David & Skodeberg, Torben M., 2002. "Analyzing rating transitions and rating drift with continuous observations," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 423-444, March.
- Nickell, Pamela & Perraudin, William & Varotto, Simone, 2000.
"Stability of rating transitions,"
Journal of Banking & Finance,
Elsevier, vol. 24(1-2), pages 203-227, January.
- Jafry, Yusuf & Schuermann, Til, 2004. "Measurement, estimation and comparison of credit migration matrices," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2603-2639, November.
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