Recent literature focuses on the basic components of credit risk, and mainly the interaction between systematic and idiosyncratic risk in determining credit risk level (see Crouhy, Galai & Mark (1999)). Namely, the influence of business cycle (that represents the systematic risk factor) on credit risk is investigated while studying the impact of key macroeconomic indicators. On one hand, many authors investigated and emphasized the systematic nature and component of credit risk (see Jarrow & Turnbull (1995a,b), Das & Tufano (1996), Duffee (1998), Jarrow & Turnbull (2000), Elton, Gruber, Agrawal & Mann (2001), Hillegeist et al. (2002), Bongini et al. (2002), Allen & Saunders (2003), Xie, Wu & Shi (2004), Koopman, Lucas & Klaassen (2005), Dionne et al. (2006)).
The obtained results support the significant role of both systematic risk and relevant market and/or macroeconomic indicators in explaining the level and evolution of credit risk fundamentals. On the other hand, other authors disentangled credit risk into two components such as systematic/market risk and idiosyncratic/specific risk (see Dichev (1998), Wilson (1998), Nickell et al. (2000), Baraton & Cuillere (2001), Crouhy, Galai & Mark (2000, 2001), Delianedis & Geske (2001), Spahr et al. (2002), Ericsson & Renault (2003), Gatfaoui (2003), Aramov et al. (2004), Gatfaoui (2005), Jarrow, Lando & Yu (2005), Bakshi, Madan & Zhang (2006)). Related issues support that credit risk results from the combination of financial and macroeconomic risk factors (i.e., market and systematic risk factors) with idiosyncratic and firm-specific risk factors (e.g., liquidity risk).
More recently, various sophisticated latent factor models arose to study the relationship prevailing between credit risk and market risk, or equivalently business cycle (see Galgliardini & Gouriéroux (2004), Koopman, Lucas & Daniels (2005)). One-factor models attempt to account for the market risk side while assessing credit risk (see Cipollini & Missaglia (2005), Hamerle, Liebig & Scheule (2004)) whereas multi-factor models focus on observed and unobserved latent macroeconomic factors (i.e., business cycle) underlying credit risk evolution (see Hui, Lo & Huang (2003), Tasche (2005), Berardi & Trova (2005)). Indeed, incorporating latent factors improves model accuracy and reliability while assessing credit risk (see Amato & Luisi (2006), Jakubik (2006)). With regard to corporate bonds and credit spreads, Elizalde (2005) shows that credit risk results essentially from common risk factors that affect all firms.
Credit risk is decomposed into different unobservable factors among which a single common factor accounts for more than 50% of firm credit risk levels. Moreover, this single common factor is strongly correlated with known US stock market indices. In the same line, Saita (2006) implements a reduced-form latent factor model while studying credit spreads versus risk-free rates. The model incorporates macroeconomic variables as well as firm-specific factors such as leverage and firm volatility. This way, the author shows that expected excess returns on corporate bonds (i.e., credit spreads) depend on systematic risk factors. Namely, unknown and unobserved systematic risk factors in addition to Fama & French (1993) systematic risk factors might explain a large portion of observed credit spreads (i.e., default timing and default event). Studying also corporate bond spreads, Frühwirth, Schneider & Sögner (2005) distinguish between interest rate risk, credit risk (i.e., issuer-specific risk) and liquidity risk (i.e., bond-specific risk). These components are extracted from relevant latent processes that represent both bond-specific and issuer-specific risk factors. Moreover, the correlation between the risk-free term structure and credit risk is also taken into account. Later Berndt, Lookman & Obrega (2006) investigate the link between default risk premia and both systematic observed risk factors and an unobserved latent risk factor.
Considering unexplained returns (i.e., that part of corporate bond returns, which does not result from changes in risk-free rates and expected losses), they distinguish between Fama & French (1993) systematic factors (e.g., default and term factors), Jegadeesh & Titman (1993) momentum factor, and an unobserved common latent component. Moreover, unexplained returns reveal to be independent of default probabilities, credit ratings, leverage ratios and recovery rates. With regard to failure rates, Koopman & Lucas (2005) employ a multivariate unobserved component methodology to investigate the link prevailing between macroeconomic conditions and both credit spreads and failure rates. They emphasize empirically the correlation existing between credit risk and macroeconomic state. In a similar view, Jakubik (2006) investigates the link between credit risk and business cycle. The author targets the impact of macroeconomic changes on default events. For microeconomic reasons, the author considers macro credit risk models that incorporate latent systematic risk factors in order to predict default rates.
In the light of the strong relationship between credit risk and market risk, we realize a two-stage study while investigating US credit spreads’ evolutions. First, we emphasize the global common component in all credit spreads under consideration, which represents the systematic part of credit risk at sector-, rating-, and maturity-based levels. We argue that the decomposition of credit spreads into systematic and idiosyncratic components varies across sectors, credit ratings and maturities. Second, we investigate the dynamic link that prevails between the systematic component in credit spreads and the S&P 500 stock index return. We check whether the common practice that resorts to S&P 500 stock market index as a proxy for systematic risk factor is coherent. Specifically, we address three distinct questions. Firstly, can we describe the interaction arising between credit risk and market risk over time? Secondly, is S&P 500 index a convenient proxy for the financial market when assessing the systematic component of US credit spreads? Thirdly, when this is not the case, can we use the link prevailing between credit spreads and S&P 500 index to extract or estimate the systematic part of credit spreads?.
The paper is organized as follows. Section 2 introduces the data and some related empirical features. Section 3 presents the methodology employed to extract the common latent component in credit spreads in the light of three risk dimensions, namely economic sector, credit rating and maturity. Section 4 investigates the link between the common latent component in credit spreads and S&P 500 stock index along with the three previous risk dimensions. Finally, section 5 draws some concluding remarks and proposes future research extensions.
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