Post by Sapphire Capital on Jul 11, 2008 6:45:17 GMT 4
The Complete Picture of Credit Default Swap Spreads - A Quantile Regression Approach
PEDRO PIRES
ISCTE Business School
JOÃO PEDRO PEREIRA
ISCTE Business School
LUIS F. MARTINS
Pennsylvania State University - Department of Economics
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March 11, 2008
Abstract:
This paper uses quantile regressions to study the determinants of Credit Default Swap (CDS) spreads. This approach allows the characterization of the entire conditional distribution of credit spreads, instead of just the mean as with least squares regressions. First, we find that CDS spreads are strongly determined by the firm's equity implied volatility and put option skew. However, both the coefficients on those variables and the goodness-of-fit of the model strongly depend on whether the firm is in the left tail (high-grade firms) or in the right tail (high-yield firms) of the CDS distribution. Our results thus suggest that some previous studies may have been overly optimistic on the judgment of the relative success of their empirical models. Furthermore, our findings imply that hedging and capital structure arbitrage strategies are expected to be more effective when applied to firms with high CDS spreads. Second, this paper shows that CDS bid-ask spreads contain significant information for credit pricing. Finally, we show that the shape of the conditional distribution of CDS spreads changes abruptly for different levels of implied volatility, which highlights the advantage of integrating models of stochastic equity volatility within credit Value-at-Risk frameworks.
papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1125265_code24319.pdf?abstractid=1125265&mirid=2
PEDRO PIRES
ISCTE Business School
JOÃO PEDRO PEREIRA
ISCTE Business School
LUIS F. MARTINS
Pennsylvania State University - Department of Economics
--------------------------------------------------------------------------------
March 11, 2008
Abstract:
This paper uses quantile regressions to study the determinants of Credit Default Swap (CDS) spreads. This approach allows the characterization of the entire conditional distribution of credit spreads, instead of just the mean as with least squares regressions. First, we find that CDS spreads are strongly determined by the firm's equity implied volatility and put option skew. However, both the coefficients on those variables and the goodness-of-fit of the model strongly depend on whether the firm is in the left tail (high-grade firms) or in the right tail (high-yield firms) of the CDS distribution. Our results thus suggest that some previous studies may have been overly optimistic on the judgment of the relative success of their empirical models. Furthermore, our findings imply that hedging and capital structure arbitrage strategies are expected to be more effective when applied to firms with high CDS spreads. Second, this paper shows that CDS bid-ask spreads contain significant information for credit pricing. Finally, we show that the shape of the conditional distribution of CDS spreads changes abruptly for different levels of implied volatility, which highlights the advantage of integrating models of stochastic equity volatility within credit Value-at-Risk frameworks.
papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1125265_code24319.pdf?abstractid=1125265&mirid=2