The Multi-State Latent Factor Intensity Model for Credit Rating Transitions

By S. J. Koopman, André Lucas, André A. Monteiro. 2008

173 citations recorded by the source corpus.

Subfields: Accounting, Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/906818f31ae523622ba29b96ff920de9bb992ac1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Accounting

1. Alexander J. McNeil
2. Jonathan Wendin
3. Drew D. Creal
4. André Lucas
5. S. J. Koopman
6. B. Schwaab

In Finance

1. André Lucas
2. S. J. Koopman
3. B. Schwaab
4. Jonathan Wendin
5. Drew D. Creal
6. Alexander J. McNeil
7. Andrew J. Patton
8. Francisco Blasques

In Statistics and Probability

1. André Lucas
2. S. J. Koopman
3. B. Schwaab
4. Jonathan Wendin
5. Alexander J. McNeil
6. Drew D. Creal
7. Francisco Blasques
8. Paul Embrechts

Citations in the corpus

• GENERALIZED AUTOREGRESSIVE SCORE MODELS WITH APPLICATIONS (2013, methodology): “We obtain similar estimated patterns (not shown) for the three factors in ft compared to the more involved parameter driven model of Koopman et al. (2008) with three factors.”
• Dependent Credit Migrations (2006, methodology): “Koopman, Lucas, and Monteiro (2005) use simulated ML to fit a duration model with stochastic intensity to credit transition data.”
• Multiperiod Corporate Default Prediction - A Forward Intensity Approach (2012, unknown): “A potential quick fix is to introduce the frailty effect as suggested in the previous literature such as Koopman, et al (2008) and Duffie, et al (2009) or to employ the regime-switching approach as in Chuang and Kuan (2010).”
• Modeling the Effect of Macroeconomic Factors on Corporate Default and Credit Rating Transitions (2012, unknown): “…reduced form approach has been widely used for credit risk analysis in both academic and real world research, e.g., Jarrow, Lando, and Turnbull (1995) and Jarrow, Lando, and Turnbull (1997), Lando and Skødeberg (2002), Duffie, Saita, and Wang (2007), Koopman et al. (2008) and Koopman et al. (2009).”
• A General Framework for Observation Driven Time-Varying Parameter Models (2008, unknown): “By following the application in Koopman, Lucas, and Monteiro (2008), we model the log intensities of these processes by λjk(t) = ηj + α ′ jft−1, (24) where ηj is the baseline intensity and αj is the vector of loadings for ft which is the vector of dynamic factors and specified by the GAS(1,1)…”
• Modeling frailty-correlated defaults using many macroeconomic covariates (2011, methodology): “For this reason McNeil and Wendin (2007) and Duffie et al. (2009) employ Bayesian inference methods, while Koopman et al. (2008) and Koopman and Lucas (2008) rely on a Monte Carlo maximum likelihood approach.”