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Credit Risk Models III: Reconciliation Reduced – Structural Models

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  • Abel Elizalde

Abstract

In recent years, some papers have tried to bridge the gap between the two main approaches in credit risk modelling: structural and reduced form models. Based on incomplete information versions of standard structural models, they are able to obtain reduced form models in which the intensity of default is not given exogenously but determined endogenously within the model and it is a function of the firm’s characteristics and the level of information that investors posses. The key element to link both approaches lies in the model’s information assumptions. Using a specification of a structural model where investors do not have complete information about the dynamics of the processes which trigger the firm’s default, these models derive a cumulative rate of default consistent with a reduced form model. This paper pretends to be an introduction to this literature, providing some of the basic insights of the modelling structure and the main conclusion and results.

Suggested Citation

  • Abel Elizalde, 2006. "Credit Risk Models III: Reconciliation Reduced – Structural Models," Working Papers wp2006_0607, CEMFI.
    • Handle: RePEc:cmf:wpaper:wp2006_0607
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    References listed on IDEAS

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    Cited by:

    1. Trueck, Stefan & Rachev, Svetlozar T., 2008. "Rating Based Modeling of Credit Risk," Elsevier Monographs, Elsevier, edition 1, number 9780123736833.
    2. Tijana Matejić & Snežana Knežević & Vesna Bogojević Arsić & Tijana Obradović & Stefan Milojević & Miljan Adamović & Aleksandra Mitrović & Marko Milašinović & Dragoljub Simonović & Goran Milošević & Ma, 2022. "Assessing the Impact of the COVID-19 Crisis on Hotel Industry Bankruptcy Risk through Novel Forecasting Models," Sustainability, MDPI, vol. 14(8), pages 1-44, April.
    3. Andreea Costea, 2017. "A Quantitative Approach to Credit Risk Management in the Underwriting Process for the Retail Portfolio," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 20(63), pages 157-186, March.
    4. Joachim Sicking & Thomas Guhr & Rudi Schafer, 2016. "Concurrent Credit Portfolio Losses," Papers 1604.06917, arXiv.org, revised Jan 2017.
    5. Joachim Sicking & Thomas Guhr & Rudi Schäfer, 2018. "Concurrent credit portfolio losses," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-20, February.

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