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Credit risk enhancement in a network of interdependent firms

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  • Neu, Peter
  • Kühn, Reimer

Abstract

We generalize existing structural models for credit risk to capture the impact of counterparty defaults on economic capital allocated to banks’ loan portfolios. Exploring the analogy to a lattice gas model from physics, correlations between sequential defaults are modeled as due to functionally defined, heterogeneous couplings between mutually dependent counterparties. We show that—already for moderate micro-economic dependencies—counterparty risk results in a fattening of the tails in the portfolio loss distribution. In particular, for stronger mutually supportive relationship between the firms, collective phenomena such as bursts and avalanches of defaults can be observed in the model. In this context, traditional credit risk models are inadequate because they underestimate the required capital buffer. Our model setting is particularly applicable for doing stress analyses of credit risk in loan portfolios.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:342:y:2004:i:3:p:639-655
    DOI: 10.1016/j.physa.2004.05.062
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    Cited by:

    1. Pawe{l} Sieczka & Didier Sornette & Janusz A. Ho{l}yst, 2010. "The Lehman Brothers Effect and Bankruptcy Cascades," Papers 1002.1070, arXiv.org, revised Sep 2011.
    2. S. Heise & R. Kühn, 2012. "Derivatives and credit contagion in interconnected networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 85(4), pages 1-19, April.
    3. Carlos Castro & Juan S. Ordoñez & Sergio Preciado, 2016. "Network externalities across financial institutions," Documentos de Trabajo 14287, Universidad del Rosario.
    4. 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.
    5. Didier Cossin & Henry Schellhorn, 2007. "Credit Risk in a Network Economy," Management Science, INFORMS, vol. 53(10), pages 1604-1617, October.
    6. Hsiang Hui Chu & Yi Fang Chung, 2016. "Analysis of the Contagion Effect to the Credit Derivative Valuation," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 6(10), pages 571-582, October.
    7. 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.
    8. Lee, Sangwook & Kim, Min Jae & Lee, Sun Young & Kim, Soo Yong & Ban, Joon Hwa, 2013. "The effect of the subprime crisis on the credit risk in global scale," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2060-2071.
    9. 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.
    10. Xiaowo Wu & Jiangwei Tu & Boru Liu & Xi Zhou & Yanxiong Wu, 2022. "Credit Risk Evaluation of Forest Farmers under Internet Crowdfunding Mode: The Case of China’s Collective Forest Regions," Sustainability, MDPI, vol. 14(10), pages 1-17, May.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.

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