Testing Homogeneity of Time-Continuous Rating Transitions
Banks could achieve substantial improvements of their portfolio credit risk assessment by estimating rating transition matrices within a time-continuous Markov model, thereby using continuous-time rating transitions provided by internal rating systems instead of discrete-time rating information. A non-parametric test for the hypothesis of time-homogeneity is developed. The alternative hypothesis is multiple structural change of transition intensities, i.e. time-varying transition probabilities. The partial-likelihood ratio for the multivariate counting process of rating transitions is shown to be asymptotically c2 -distributed. A Monte Carlo simulation finds both size and power to be adequate for our example. We analyze transitions in credit-ratings in a rating system with 8 rating states and 2743 transitions for 3699 obligors observed over seven years. The test rejects the homogeneity hypothesis at all conventional levels of significance.
|Date of creation:||2005|
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- 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.
- Calem, Paul S. & LaCour-Little, Michael, 2004. "Risk-based capital requirements for mortgage loans," Journal of Banking & Finance, Elsevier, vol. 28(3), pages 647-672, 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.
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