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| Exploring for the Determinants of Credit Risk in Credit Default Swap Transaction Data: Is fixed-income markets information sufficient to evaluate credit risk by Daniel Aunon-Nerin of the University of Lausanne & Fame, December 2002 Abstract: We investigate the influence of various fundamental variables on a cross-section of credit default swap transaction data. Credit default swap rates can be seen as a superior proxy for credit risk than bond spreads are. Because we have transaction prices rather than quotes, we have thus observations of financial markets' assessment of credit risk. Therefore our finings are relevant not only for the understanding of credit default swaps but for credit risk in general. The fundamental variables include fixed-income market data such as ratings, interest rate data, and bond spreads as well as equity market data such as variance and market leverage (so called "structural variables"). We test for the stability of the influence of the different fundamental variables along several lines. We find evidence that most of the variables predicted by credit risk pricing theories have a significant impact on the observed levels of credit default prices. We also provide an international analysis of corporate credit risk, as half of our corporate sample is not US based, as well as some results on sovereign credit risk. Using this information we are able to explain a significant portion of the cross-sectional variation in our sample with adjusted R2 reaching 82% using the variables predicted by classical theoretical models. However there are important behavioral differences between high rated and low rated underlyings, sovereign and corporate underlyings and underlyings from different markets (US vs no US). We analyze these differences. Strong results show the importance of considering so called "structural variables" as well as stochastic interest rates along with classical ratings when pricing credit risk overall. Wee implement a reduced-form model and analyze the errors obtained. Equity market variables seem to explain a large part of the errors. Overall, we document the importance of taking into account equity markets when doing credit risk analysis. JEL Classification: G12, G13, G15. |
