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Least Impulse Response Estimator for Stress Test Exercises

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  • Christian Gourieroux

    (CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - ENSAE ParisTech - École Nationale de la Statistique et de l'Administration Économique - CNRS - Centre National de la Recherche Scientifique)

  • Yang Lu

    () (CRENAU - Centre de recherche nantais Architectures Urbanités - AAU - Ambiances, Architectures, Urbanités - ECN - École Centrale de Nantes - ENSAG - École nationale supérieure d'architecture de Grenoble - ENSA Nantes - École nationale supérieure d'architecture de Nantes - CNRS - Centre National de la Recherche Scientifique - MCC - Ministère de la Culture et de la Communication)

Abstract

We introduce new semi-parametric models for the analysis of rates and proportions, such as proportions of default, (expected) loss-given-default and credit conversion factor encountered in credit risk analysis. These models are especially convenient for the stress test exercises demanded in the current prudential regulation. We show that the Least Impulse Response Estimator, which minimizes the estimated effect of a stress, leads to consistent parameter estimates. The new models with their associated estimation method are compared with the other approaches currently proposed in the literature such as the beta and logistic regressions. The approach is illustrated by both simulation experiments and the case study of a retail P2P lending portfolio.

Suggested Citation

  • Christian Gourieroux & Yang Lu, 2019. "Least Impulse Response Estimator for Stress Test Exercises," Working Papers hal-02089698, HAL.
  • Handle: RePEc:hal:wpaper:hal-02089698
    Note: View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-02089698
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    References listed on IDEAS

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    1. Guo, Yanhong & Zhou, Wenjun & Luo, Chunyu & Liu, Chuanren & Xiong, Hui, 2016. "Instance-based credit risk assessment for investment decisions in P2P lending," European Journal of Operational Research, Elsevier, vol. 249(2), pages 417-426.
    2. Bruche, Max & González-Aguado, Carlos, 2010. "Recovery rates, default probabilities, and the credit cycle," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 754-764, April.
    3. repec:wly:emetrp:v:87:y:2019:i:1:p:327-345 is not listed on IDEAS
    4. C. Gouriéroux & A. Monfort & J.‐M. Zakoïan, 2019. "Consistent Pseudo‐Maximum Likelihood Estimators and Groups of Transformations," Econometrica, Econometric Society, vol. 87(1), pages 327-345, January.
    5. repec:wly:apsmbi:v:30:y:2014:i:2:p:99-114 is not listed on IDEAS
    6. Calabrese, Raffaella & Zenga, Michele, 2010. "Bank loan recovery rates: Measuring and nonparametric density estimation," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 903-911, May.
    7. repec:eee:econom:v:200:y:2017:i:1:p:118-134 is not listed on IDEAS
    8. Ospina, Raydonal & Ferrari, Silvia L.P., 2012. "A general class of zero-or-one inflated beta regression models," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1609-1623.
    9. Calabrese, Raffaella, 2014. "Downturn Loss Given Default: Mixture distribution estimation," European Journal of Operational Research, Elsevier, vol. 237(1), pages 271-277.
    10. Renault, Olivier & Scaillet, Olivier, 2004. "On the way to recovery: A nonparametric bias free estimation of recovery rate densities," Journal of Banking & Finance, Elsevier, vol. 28(12), pages 2915-2931, December.
    11. Bellotti, Tony & Crook, Jonathan, 2012. "Loss given default models incorporating macroeconomic variables for credit cards," International Journal of Forecasting, Elsevier, vol. 28(1), pages 171-182.
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    More about this item

    Keywords

    Basel Regulation; Stress Test; (Expected) Loss-Given-Default; Impulse Response; Credit Scoring; Pseudo-Maximum Likelihood; LIR Estimation; Beta Regression; Moebius Transformation;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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