Anchoring Credit Default Swap Spreads to Firm Fundamentals∗

This paper examines the capability of firm fundamentals in explaining the cross-sectional variation of credit default swap spreads. We start with the Merton (1974) model, which combines two major credit risk determinants into a distance-to-default measure. We convert the distance-to-default measure into a raw CDS valuation based on a constant hazard rate assumption and then map the raw CDS valuation to market observation via a local quadratic regression, removing the average bias of raw valuation at different risk levels. We also collect a long list of firm fundamental characteristics that are not included in the Merton-based valuation but have been shown to be informative about a firm’s credit spread, and propose a Bayesian shrinkage method to combine the Merton-based valuation with the information from this long list of fundamental characteristics. Historical analysis on 579 U.S. non-financial public firms over 351 weeks shows that the bias-corrected Merton-based valuation raises the average cross-sectional explanatory power from 49% to 65%. Incorporating additional firm fundamental characteristics further increases the average explanatory power to 77% while also making the performance more uniform over time. Furthermore, deviations between market observations and fundamental-based valuations generate statistically and economically significant forecasts on future market movements in credit default swap spreads. JEL Classification: C11, C13, C14, G12.