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Credit risk characteristics of US small business portfolios

Listed author(s):
  • Bams, Dennis
  • Pisa, Magdalena
  • Wolff, Christian C

This paper addresses issues related to industry heterogeneity, default clustering and parameter uncertainty of capital requirements in US retail loan portfolios. Using a multi-factor model of credit risk, we show that the Basel II capital requirements overstate the riskiness of small businesses. Retail exposures are a much safer investment than the regulator would suggest. We find that sensitivity to the common risk factors is low and that small business risk is predominantly a reflection of idiosyncratic risk. Our results show that only 0.00-3.39% of the asset variability is explained by economy-wide risk factors. The remaining 96.61%-100.00% of small business risk is due to changes in the firm-specific characteristics. Moreover, both expected and unexpected losses are time dependent. Their shifts over the course of financial crisis cause uncertainty in the provisions level and capital requirements. Importantly, our estimates of asset correlations are significantly lower than any available estimates for corporate firms. Our results are based on a new, representative dataset of US retail businesses from 2005 to 2011 and give fundamental insights into the US economy.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 10889.

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Date of creation: Oct 2015
Handle: RePEc:cpr:ceprdp:10889
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  1. Glennon, Dennis & Nigro, Peter, 2005. "Measuring the Default Risk of Small Business Loans: A Survival Analysis Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(5), pages 923-947, October.
  2. Duffie, Darrell & Saita, Leandro & Wang, Ke, 2007. "Multi-period corporate default prediction with stochastic covariates," Journal of Financial Economics, Elsevier, vol. 83(3), pages 635-665, March.
  3. Darrell Duffie & Andreas Eckner & Guillaume Horel & Leandro Saita, 2009. "Frailty Correlated Default," Journal of Finance, American Finance Association, vol. 64(5), pages 2089-2123, October.
  4. Lopez, Jose A., 2004. "The empirical relationship between average asset correlation, firm probability of default, and asset size," Journal of Financial Intermediation, Elsevier, vol. 13(2), pages 265-283, April.
  5. Dietsch, Michel & Petey, Joel, 2002. "The credit risk in SME loans portfolios: Modeling issues, pricing, and capital requirements," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 303-322, March.
  6. Antje Berndt & Peter Ritchken & Zhiqiang Sun, 2010. "On Correlation and Default Clustering in Credit Markets," Review of Financial Studies, Society for Financial Studies, vol. 23(7), pages 2680-2729, July.
  7. McNeil, Alexander J. & Wendin, Jonathan P., 2007. "Bayesian inference for generalized linear mixed models of portfolio credit risk," Journal of Empirical Finance, Elsevier, vol. 14(2), pages 131-149, March.
  8. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
  9. Gordy, Michael B., 2000. "A comparative anatomy of credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 119-149, January.
  10. 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..
  11. Giesecke, Kay, 2006. "Default and information," Journal of Economic Dynamics and Control, Elsevier, vol. 30(11), pages 2281-2303, November.
  12. Sreedhar T. Bharath & Tyler Shumway, 2008. "Forecasting Default with the Merton Distance to Default Model," Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1339-1369, May.
  13. Philippe Jorion & Gaiyan Zhang, 2009. "Credit Contagion from Counterparty Risk," Journal of Finance, American Finance Association, vol. 64(5), pages 2053-2087, October.
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