The Determinants of Credit Spread Changes

Abstract

Using dealer's quotes and transactions prices on straight industrial bonds, we investigate the determinants of credit spread changes. Variables that should in theory determine credit spread changes have rather limited explanatory power. Further, the residuals from this regression are highly cross-correlated, and principal components analysis implies they are mostly driven by a single common factor. Although we consider several macroeconomic and financial variables as candidate proxies, we cannot explain this common systematic component. Our results suggest that monthly credit spread changes are principally driven by local supply0 demand shocks that are independent of both credit-risk factors and standard proxies for liquidity.

Concentrated Capital Losses and the Pricing of Corporate Credit Risk

“…Examples of work in this area include Duffee (1998), Elton, Gruber, Agrawal, and Mann (2001), Collin-Dufresne, Goldstein, and Martin (2001). A common conclusion of these studies is variables that measure fundamental default risk, such as those from structural models of credit, explain a surprisingly low amount of credit spread variation.…”

Latent liquidity: A new measure of liquidity, with an application to corporate bonds

“…3 For instance, see Duffie and Singleton (1997), Elton, Gruber, Agrawal, and Mann (2001), Colin-Dufresne, Goldstein, and Martin (2001), Houweling, Mentink, and Vorst (2003), Huang and Huang (2003), Perraudin and Taylor (2003), Chen, Lesmond, and Wei (2006), Edwards, Harris, and Piwowar (2006), Eom, Helwege, and Huang (2004), Liu, Longstaff, and Mandell (2004), Longstaff, Mithal, and Neis (2005), and De Jong and Driessen (2005). 4 For example, Edwards, Harris, and Piwowar (2006) show that of the 70; 000þ corporate bonds outstanding in 2004, less than 17,000 experienced more than 9 trades that year.…”

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

“…Indeed, the goodness-of-fit difference between these four performance measures and the five market categories has widened substantially to approximately 37%. 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.…”