Pricing Derivatives on Financial Securities Subject to Credit Risk

Jarrow, Robert A.; Turnbull, Stuart M.

doi:10.1111/j.1540-6261.1995.tb05167.x

Cited by 1,504 publications

(741 citation statements)

References 35 publications

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“…In related studies, Skinner and Diaz (2003) look at early CDS prices from September 1997 to February 1999 for 31 CDS contracts. They compare the pricing results of the Duffie and Singleton (1999) and Jarrow and Turnbull (1995) models. Blanco, Brennan, and Marsh (2004) compare the CDS spreads with credit spreads derived from corporate bond yields and find that overall the two sources of spreads match each other well.…”

Section: Background Information On Credit Default Swap Spreadsmentioning

confidence: 99%

Dynamic Interactions Between Interest Rate, Credit, and Liquidity Risks: Theory and Evidence from the Term Structure of Credit Default Swap Spreads

Chen

Cheng

2005

SSRN Journal

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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...

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Section: Background Information On Credit Default Swap Spreadsmentioning

confidence: 99%

Dynamic Interactions Between Interest Rate, Credit, and Liquidity Risks: Theory and Evidence from the Term Structure of Credit Default Swap Spreads

Chen

Cheng

2005

SSRN Journal

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“…To model the former, we apply a structural model, which originates in [11] and in which default happens when the asset value of a company falls below its liabilities (Alternative obligor-specific default risk models are reduced form (or intensity) models, see [12,13]. For a comparison of both model classes, see [14] or [15].…”

Section: Introductionmentioning

confidence: 99%

Application of Vine Copulas to Credit Portfolio Risk Modeling

Geidosch¹,

Fischer

2016

JRFM

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Abstract:In this paper, we demonstrate the superiority of vine copulas over conventional copulas when modeling the dependence structure of a credit portfolio. We show statistical and economic implications of replacing conventional copulas by vine copulas for a subportfolio of the Euro Stoxx 50 and the S&P 500 companies, respectively. Our study includes D-vines and R-vines where the bivariate building blocks are chosen from the Gaussian, the t and the Clayton family. Our findings are (i) the conventional Gauss copula is deficient in modeling the dependence structure of a credit portfolio and economic capital is seriously underestimated; (ii) D-vine structures offer a better statistical fit to the data than classical copulas, but underestimate economic capital compared to R-vines; (iii) when mixing different copula families in an R-vine structure, the best statistical fit to the data can be achieved which corresponds to the most reliable estimate for economic capital.

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“…A default event associated with a single firm occurs as in intensity-based models introduced by, among others, Artzner and Delbaen [1] , Madan and Unal [26], Lando [24] and Jarrow and Turnbull [21]. However our valuation mechanism incorporates information from the firm's stock price.…”

Section: General Modelmentioning

confidence: 99%

Utility valuation of multi-name credit derivatives and application to CDOs

Sircar

Zariphopoulou

2009

Quantitative Finance

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We study the impact of risk-aversion on the valuation of credit derivatives. Using the technology of utility-indifference pricing in intensity-based models of default risk, we analyze resulting yield spreads in multiname credit derivatives, particularly CDOs. We study first the idealized problem with constant intensities where solutions are essentially explicit. We also give the large portfolio asymptotics for this problem. We then analyze the case where the firms have stochastic default intensities driven by a common factor, which can be viewed as another extreme from the independent case. This involves the numerical solution of a system of reaction-diffusion PDEs. We observe that the nonlinearity of the utility-indifference valuation mechanism enhances the effective correlation between the times of the credit events of the various firms leading to non-trivial senior tranche spreads, as often seen from market data.

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Pricing Derivatives on Financial Securities Subject to Credit Risk

Cited by 1,504 publications

References 35 publications

Dynamic Interactions Between Interest Rate, Credit, and Liquidity Risks: Theory and Evidence from the Term Structure of Credit Default Swap Spreads

Dynamic Interactions Between Interest Rate, Credit, and Liquidity Risks: Theory and Evidence from the Term Structure of Credit Default Swap Spreads

Application of Vine Copulas to Credit Portfolio Risk Modeling

Utility valuation of multi-name credit derivatives and application to CDOs

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