Using a large data set on credit default swaps, we study how default risk interacts with interest-rate risk and liquidity risk to jointly determine the term structure of credit spreads. We classify the reference companies into two broad industry sectors, two broad credit rating classes, and two liquidity groups. We develop a class of dynamic term structure models that include (i) two benchmark interest-rate factors to capture the libor and swap rates term structure, (ii) two credit-risk factors to capture the credit swap spreads of high-liquidity group of each industry and rating class, and (iii) both an additional credit-risk factor and a liquidity-risk factor to capture the difference between the high-and low-liquidity groups.Estimation shows that companies in different industry and credit rating classes have different credit-risk dynamics. Nevertheless, in all cases, credit risks exhibit intricate dynamic interactions with the interestrate factors. Interest-rate factors both affect credit spreads simultaneously, and impact subsequent moves in the credit-risk factors. Within each industry and credit rating class, we also find that the average credit default swap spreads for the high-liquidity group are significantly higher than for the low-liquidity group. Estimation shows that the difference is driven by both credit risk and liquidity differences. The low-liquidity group has a lower default arrival rate and also a much heavier discounting induced by the liquidity risk.JEL CLASSIFICATION CODES: E43, G12, G13, C51.KEY WORDS: Credit default swap; credit risk; credit premium; term structure; interest rate risk; liquidity risk; liquidity premium; maximum likelihood estimation.
Dynamic Interactions Between Interest Rate, Credit, and Liquidity Risks: Theory and Evidence from the Term Structure of Credit Default Swap SpreadsIt is important to understand how credit risk interacts with interest-rate risk and liquidity risk in determining the term structure of credit spreads on different reference entities. Nevertheless, limited data availability has severely hindered the understanding. Since defaults are rare events that often lead to termination or restructuring of the underlying reference entity, researchers need to rely heavily on cross-sectional averages of different entities over a long history to obtain any reasonable estimates of statistical default probabilities.Although corporate bond prices contain useful information on the default probability and the price of credit risk, the information is often mingled with the pricing of the underlying interest-rate risk and other factors such as liquidity and tax. 1 The recent development in credit derivatives provides us with an excellent opportunity to better understand the pricing of credit risk, its interactions with interest-rate risk and liquidity, and the impacts on the term structure of credit spreads. The most widely traded credit derivative is in the form of credit default swap (CDS), written on a reference entity such as a sovereign country or a cor...