Antoine Djogbenou, Christian Gouriéroux, Joann Jasiak, Maygol Bandehali
arXiv 19 Sep 2021 · Econometrics · publishedJournal of Financial Econometrics (2023) · 1 citations (OpenAlex)
arXiv:2109.09043 · PDF · DOI · OpenAlex · Extracted main text
We introduce the conditional Maximum Composite Likelihood (MCL) estimation method for the stochastic factor ordered Probit model of credit rating transitions of firms. This model is recommended for internal credit risk assessment procedures in banks and financial institutions under the Basel III regulations. Its exact likelihood function involves a high-dimensional integral, which can be approximated numerically before maximization. However, the estimated migration risk and required capital tend to be sensitive to the quality of this approximation, potentially leading to statistical regulatory arbitrage. The proposed conditional MCL estimator circumvents this problem and maximizes the composite log-likelihood of the factor ordered Probit model. We present three conditional MCL estimators of different complexity and examine their consistency and asymptotic normality when n and T tend to infinity. The performance of these estimators at finite T is examined and compared with a granularity-based approach in a simulation study. The use of the MCL estimator is also illustrated in an empirical application.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Feng, D., Gouriéroux, C., and J., Jasiak (2008) The Ordered Qualitative Model for Credit Rating Transitions | 1.000 | 7 | 3 | 100% |
| 2 | Gagliardini, P., and C., Gouriéroux (2014) Efficiency in Large Dynamic Panel Models with Common Factors | 1.000 | 5 | 4 | 100% |
| 3 | Gagliardini, P., and C., Gouriéroux (2005) Stochastic Migration Models with Application to Corporate Risk | 1.000 | 5 | 3 | 100% |
| 4 | Gagliardini, P., and C., Gouriéroux (2015) Granularity Theory with Applications to Finance and Insurance | 0.950 | 7 | 4 | 86% |
| 5 | Varian, C., Reid, N., and D., Firth (2011) An Overview of Composite Likelihood Methods | 0.843 | 3 | 3 | 100% |
| 6 | European Banking Authority (2012) Guidelines on the Incremental Default and Migration Risk Change (IRC) | 0.811 | 4 | 2 | 100% |
| 7 | Cox, D., and N., Reid (2004) A Note on Pseudolikelihood Constructed from Marginal Densities | 0.737 | 3 | 2 | 100% |
| 8 | Azizpour, S., Giesecke, K., and G., Schwenkler (2018) Exploring the Sources of Default Clustering | 0.644 | 2 | 2 | 100% |
| 9 | Grippa, P., and L. Gornicka (2016) | 0.644 | 2 | 2 | 100% |
| 10 | Vasicek, O (2015) Probability Loss and Loan Portfolio | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 46 scored citations.