1. Short- and Long-term Default Risks Implied in the Term Structure of CDS Spreads Kuate Kamga & Wilde Credit risk characteristics of US small business portfolios Bams, Pisa & Wolff Hugues Pirotte ULB, National Bank of Belgium, FinMetrics Session on Credit Risk

2. Credit risk characteristics of US small business portfolios Bams, Pisa & Wolff

3. Idea H. Pirotte 3 240’000 firms on average Idiosyncratic component

4. Idea (2)  Definition of default: thresholds  Theoretical joint default proba  Empirical joint default proba H. Pirotte 4

5. Process 1)Subsampling exercise based on the Vasicek Model. »Top-down approach »Based on the homogeneity/heterogeneity »Testing three dimensions: credit rating, industry, size (#employees). Non-monotonic relationship between size and asset correlation. 2)Verification of global common factor »Violated 3)Analysis of parameters for small businesses »Only max 3.4% if explained by common factors Default is more “certain” in crisis times. Huge diversification of dataset. »Very low asset correlations »EL assoc. with PDs, and UL with asset correlations… »Materiality on equity buffer: on average ~1.87% less than what BII predicts 4)Verification that similar levels to Basel II are obtained for corporates. H. Pirotte 5

6. Questions/Comments 1)Very interesting study: »Using a top-down approach for homogenous obligor class definition »Multi-common-factor »Huge DB of US small businesses 2)Survivorship bias (?) »Could use a cohort-type of analysis 3)Firm size effect not significant for subsampling (not adding additional heterogeneity) »Within the sample of small firms… »Why not joining both the corporate and small businesses (?) »Data description shows differentiated behavior (10% for 100e). Thus… 4)Data granularity »Banks would think of their portfolio in terms of business volume 25% of sample with exposures below1’000$ 99.75% below 1 million. »What about weighting by exposure (?) – just to check 5)Smaller »Wording complexity of pages 13-14 »Asset correlations within the obligor class vs. “in general”. »Bottom of page 17 (..”thus”…) H. Pirotte 6

7. Other refs  Blanchflower, David G., Phillip B. Levine, and David J. Zimmerman. "Discrimination in the small-business credit market." Review of Economics and Statistics 85, no. 4 (2003): 930-943.  Altman, Edward I., and Gabriele Sabato. "Modelling credit risk for SMEs: Evidence from the US market." Abacus 43, no. 3 (2007): 332-357.  Altman, Edward I., and Gabriele Sabato. "Effects of the new Basel capital accord on bank capital requirements for SMEs." Journal of Financial Services Research 28, no. 1-3 (2005): 15-42.  Jacobson, Tor, Jesper Lindé, and Kasper Roszbach. "Credit risk versus capital requirements under Basel II: are SME loans and retail credit really different?."Journal of Financial Services Research 28, no. 1-3 (2005): 43- 75. H. Pirotte 7

8. Short- and Long-term Default Risks Implied in the Term Structure of CDS Spreads Kuate Kamga & Wilde

9. Positioning 1)Absence of analysis of short-term default risk in CDS markets. 2)Model to capture that since “short-term maturity” CDSs are still too “long”. Default intensity at PIT vs. default intensity at distant future (if survived) 3)Examination of behavior on various periods 4)Analysis of the determinants of both ST and LT components. ST factor driven by macro flows, LT factor is more firm-specific. 5)Find recovery rates Bimodal cross-sectional distributions. H. Pirotte 9

10. Ideas  Analogy with PIT vs. TTC ratings.  Contrast between inference from CDS and from bond data. H. Pirotte 10

11. Questions  Heterogeneity inter-sector  homogeneity intra-sector?  Government interventions  event study checking? »Would suggest a more moderate speech  Default spread  spread between IG and HY bonds (?)  Conclusion »Short-term component  IVol from Equity option, default spread »Long-term component  ratings, rf rates.  What ratings?  Capturing the evolution of the implied default risk vs. the evolution of the credit risk premia (uncertainty vs. risk perception). H. Pirotte 11

12. Remarks  These reports point out that long-term investors face unpredicted short-term liabilities and larger expected losses during the crisis  larger than what…  Be careful about saying you are a precursor… »“…in terms of the approach that we use to model short- and long- term default risks”  Be more precise on sentences like »“…since counterparty risk is proven not to have an economically significant effect on CDS prices (see e.g. Arora, Gandhi, and Longstaff (2012))”.  Check English H. Pirotte 12