The Determinants of Credit Default Swap Premia

Abstract

Variables that in theory determine credit spreads have limited explanatory power in existing empirical work on corporate bond data. We investigate the linear relationship between theoretical determinants of default risk and default swap spreads. We find that estimated coefficients for a minimal set of theoretical determinants of default risk are consistent with theory and are significant statistically and economically. Volatility and leverage have substantial explanatory power in univariate and multivariate regressions. A principal component analysis of residuals and spreads indicates limited evidence for a residual common factor, confirming that the theoretical variables explain a significant amount of the variation in the data.

Determinants of Credit Default Swap Spreads: A Four-Market Panel Data Analysis

“…17 In other words, our results suggest that reference entities with lower credit ratings such as those in KOR and HKG exhibit greater explanatory power than those in other markets. Although this observation diverges from the results of Avramov, Jostova and Philipov (2007) and Ericsson et al (2009), it is in line with those of Huang and Huang (2003) and Galil et al (2014). As shown in Figure 2, regressions employing CDS spread levels as the dependent variable (Model 1) produce a set of relatively high adjusted R 2 values that range from 0.681 to 0.798, whereas those using CDS spread changes as the dependent variable (Model 2) generate relatively lower adjusted R 2 values that range from 0.056 to 0.428.…”

“…18 However, according to the redundant fixed-effects test F-statistics, 19 although Model 2 17 See, for example, ∆ROE, which has the largest difference (0.428 -0.056) = 0.372. 18 As further support for our claim, the models estimated by Galil et al (2014) and Ericsson et al (2009) using US CDS data yield only an explanatory power of 16.23% and 23%, respectively. 19 The summary of redundant fixed effects test F-statistics is available upon request.…”

“…Hypothesis One (H1) entails the testing of firm-specific factors in the CDS determination. Previous studies such as Ericsson et al (2009) and Galil et al (2014) include one firm performance related variable -leverage, in their work, our paper extends the investigation by introducing three firm performance variables. This approach adds further vigorousness to the CDS research, and it forms a major contribution of this paper to the understanding of CDS determinants.…”

“…As a major extension to Ericsson et al (2009) and Galil et al (2014), 6 three firm performance ratios are used in our study. The first ratio is return on assets (ROA), which is calculated by dividing a firm's net income (NI) by its total assets (TA).…”

Common factors in credit defaults swap markets

“…Typically, portfolio loss distributions are based on the correlating influence from such observable market-wide factors. A number of potentially observable factors from macroeconomic fundamentals have been proposed to analyze correlated defaults (Collin-Dufresne et al 2001;Benkert 2004;Ericsson et al 2009). The third research stream, however, extracts some latent/unobservable factors mainly from the principal components analysis (PCA) method to avoid a possible downward bias from estimating tail loss (Duffie et al 2009;Cesare and Guazzarotti 2010;Anderson 2008).…”