IDEAS home Printed from https://ideas.repec.org/p/vnm/wpaper/162.html
   My bibliography  Save this paper

A credit contagion model for the dynamics of the rating transitions in a SME bank loan portfolio

Author

Listed:
  • Antonella Basso

    (Department of Applied Mathematics, University of Venice)

  • Riccardo Gusso

    (Department of Applied Mathematics, University of Venice)

Abstract

In this work we analyze the effects of credit contagion on the credit quality of a portfolio of bank loans issued to SMEs. To this aim we start from the discrete time model proposed in Barro and Basso (2005), that considers the counterparty risk generated by the business relations in a network of firms, and we modify it by introducing different rating classes in order to manage the case of firms with different credit qualities. The transitions from a rating class to another occurs when a proxy for the asset value of the firm crosses some rating specific thresholds. We assume that the initial rating transition matrix of the system is known, and compute the thresholds using the probability distribution of the steady state of the model. A wide Monte Carlo simulation analysis is carried out in order to study the dynamic behaviour of the model, and in particular to analyze how the default contagion present in the model affects the output rating transition matrix of the portfolio.

Suggested Citation

  • Antonella Basso & Riccardo Gusso, 2008. "A credit contagion model for the dynamics of the rating transitions in a SME bank loan portfolio," Working Papers 162, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    • Handle: RePEc:vnm:wpaper:162
    as

    Download full text from publisher

    File URL: http://virgo.unive.it/wpideas/storage/2008wp162.pdf
    File Function: First version, 2008
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Neu, Peter & Kühn, Reimer, 2004. "Credit risk enhancement in a network of interdependent firms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 342(3), pages 639-655.
    2. Stefan Weber & Kay Giesecke, 2003. "Credit Contagion and Aggregate Losses," Computing in Economics and Finance 2003 246, Society for Computational Economics.
    3. Giesecke, Kay & Weber, Stefan, 2004. "Cyclical correlations, credit contagion, and portfolio losses," Journal of Banking & Finance, Elsevier, vol. 28(12), pages 3009-3036, December.
    4. Robert A. Jarrow & Fan Yu, 2008. "Counterparty Risk and the Pricing of Defaultable Securities," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 20, pages 481-515, World Scientific Publishing Co. Pte. Ltd..
    5. Egloff, Daniel & Leippold, Markus & Vanini, Paolo, 2007. "A simple model of credit contagion," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2475-2492, August.
    6. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Qian Qian & Yang Yang & Zong-Fang Zhou, 2019. "Research on Trade Credit Spreading and Credit Risk within the Supply Chain," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 389-411, January.
    2. Diana Barro & Antonella Basso, 2008. "A network of business relations to model counterparty risk," Working Papers 171, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    3. Didier Cossin & Henry Schellhorn, 2007. "Credit Risk in a Network Economy," Management Science, INFORMS, vol. 53(10), pages 1604-1617, October.
    4. Chen, Tingqiang & Wang, Jiepeng & Liu, Haifei & He, Yuanping, 2019. "Contagion model on counterparty credit risk in the CRT market by considering the heterogeneity of counterparties and preferential-random mixing attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 458-480.
    5. Barro, Diana & Basso, Antonella, 2010. "Credit contagion in a network of firms with spatial interaction," European Journal of Operational Research, Elsevier, vol. 205(2), pages 459-468, September.
    6. Giesecke, Kay & Weber, Stefan, 2006. "Credit contagion and aggregate losses," Journal of Economic Dynamics and Control, Elsevier, vol. 30(5), pages 741-767, May.
    7. Areski Cousin & Diana Dorobantu & Didier Rullière, 2013. "An extension of Davis and Lo's contagion model," Quantitative Finance, Taylor & Francis Journals, vol. 13(3), pages 407-420, February.
    8. Gagliardini, Patrick & Gouriéroux, Christian, 2013. "Correlated risks vs contagion in stochastic transition models," Journal of Economic Dynamics and Control, Elsevier, vol. 37(11), pages 2241-2269.
    9. Carlos Castro & Juan S. Ordoñez & Sergio Preciado, 2016. "Network externalities across financial institutions," Documentos de Trabajo 14287, Universidad del Rosario.
    10. Qian, Qian & Yang, Yang & Gu, Jing & Feng, Hairong, 2019. "Information authenticity, spreading willingness and credit risk contagion – A dual-layer network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    11. Jin-Chuan Duan & Weimin Miao, 2016. "Default Correlations and Large-Portfolio Credit Analysis," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 536-546, October.
    12. Qian, Qian & Chao, Xiangrui & Feng, Hairong, 2023. "Internal or external control? How to respond to credit risk contagion in complex enterprises network," International Review of Financial Analysis, Elsevier, vol. 87(C).
    13. Tingqiang Chen & Binqing Xiao & Haifei Liu, 2018. "Credit Risk Contagion in an Evolving Network Model Integrating Spillover Effects and Behavioral Interventions," Complexity, Hindawi, vol. 2018, pages 1-16, March.
    14. Egloff, Daniel & Leippold, Markus & Vanini, Paolo, 2007. "A simple model of credit contagion," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2475-2492, August.
    15. Batiz-Zuk, Enrique & Christodoulakis, George & Poon, Ser-Huang, 2015. "Credit contagion in the presence of non-normal shocks," International Review of Financial Analysis, Elsevier, vol. 37(C), pages 129-139.
    16. Raffaella Calabrese & Galina Andreeva & Jake Ansell, 2019. "“Birds of a Feather” Fail Together: Exploring the Nature of Dependency in SME Defaults," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 71-84, January.
    17. Tingqiang Chen & Xindan Li & Jining Wang, 2015. "Spatial Interaction Model of Credit Risk Contagion in the CRT Market," Computational Economics, Springer;Society for Computational Economics, vol. 46(4), pages 519-537, December.
    18. Ioannis Anagnostou & Sumit Sourabh & Drona Kandhai, 2018. "Incorporating Contagion in Portfolio Credit Risk Models Using Network Theory," Complexity, Hindawi, vol. 2018, pages 1-15, January.
    19. Horst, Ulrich, 2007. "Stochastic cascades, credit contagion, and large portfolio losses," Journal of Economic Behavior & Organization, Elsevier, vol. 63(1), pages 25-54, May.
    20. Bäuerle Nicole & Schmock Uwe, 2012. "Dependence properties of dynamic credit risk models," Statistics & Risk Modeling, De Gruyter, vol. 29(3), pages 243-268, August.

    More about this item

    JEL classification:

    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vnm:wpaper:162. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Marco LiCalzi (email available below). General contact details of provider: https://edirc.repec.org/data/dmvenit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.