Distressed debt prices and recovery rate estimation

Guo, Xin; Jarrow, Robert A.; Lin, Haizhi

doi:10.1007/s11147-009-9029-2

Cited by 25 publications

(24 citation statements)

References 21 publications

(42 reference statements)

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“…This concerns especially the notion of restructuring and auction mechanism. Thus, one should use historical data with caution, as emphasized in Guo et al [2008] or Verde et al [2009]. Let us also stress that as far as CDO tranche pricing is involved, we need to consider the joint distribution of default times and recovery rates across all names, which also includes the cross-sectional dependence between recovery rates, which is not usually addressed in the econometrics literature.…”

Section: Introductionmentioning

confidence: 99%

Pricing CDOs with State Dependent Stochastic Recovery Rates

et al. 2009

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Up to the 2007 crisis, research within bottom-up CDO models mainly concentrated on the dependence between defaults. However, due to the substantial increase in the market price of systemic credit risk protection, more attention has been paid to recovery rate assumptions. In this paper, we focus first on deterministic recovery rates in a factor copula framework. We use stochastic orders theory to assess the impact of a recovery markdown on CDOs and show that it leads to an increase of the expected loss on senior tranches, even though the expected loss on the portfolio is kept fixed. This result applies to a wide range of latent factor models. We then suggest introducing stochastic recovery rates in such a way that the conditional on the factor expected loss (or equivalently the large portfolio approximation) is the same as in the recovery markdown case. However, granular portfolios behave differently. We show that a markdown is associated with riskier portfolios that when using the stochastic recovery rate framework. As a consequence, the expected loss on a senior tranche is larger in the former case, whatever the attachment point. We also deal with implementation and numerical issues related to the pricing of CDOs within the stochastic recovery rate framework. Due to differences across names regarding the conditional (on the factor) losses given default, the standard recursion approach becomes problematic. We suggest approximating the conditional on the factor loss distributions, through expansions around some base distribution. Finally, we show that the independence and comonotonic cases provide some easy to compute bounds on expected losses of senior or equity tranches.

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Section: Introductionmentioning

confidence: 99%

Pricing CDOs with State Dependent Stochastic Recovery Rates

et al. 2009

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“…We derive the probability law of the economic and recorded default time. Numerical study reveals that our proposed models can better capture the features given by empirical study in Guo et al (2008) [5].…”

Section: Introductionmentioning

confidence: 90%

“…A recent empirical study by Guo, Jarrow and Lin (2008) [5] on the time-series behavior of market debt prices around the recorded default date reveals the fact that the market anticipates the default event well before default is recorded. Their statistical analysis shows that the time span between the economic and recorded default dates has a significant impact on recovery rate estimates and is important to obtaining unbiased estimates for defaultable bond prices.…”

Section: Introductionmentioning

confidence: 99%

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On Modeling Economic Default Time: A Reduced-Form Model Approach

Jiang

Ching

et al. 2014

Comput Econ

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In the aftermath of the global financial crisis, much attention has been paid to investigating the appropriateness of the current practice of default risk modeling in banking, finance and insurance industries. A recent empirical study by Guo et al. (2008) [5] shows that the time difference between the economic and recorded default dates has a significant impact on recovery rate estimates. Guo et al. (2011) [6] develop a theoretical structural firm asset value model for a firm default process that embeds the distinction of these two default times. To be more consistent with the practice, in this paper, we assume the market participants cannot observe the firm asset value directly and developed a reduced-form model to characterize the economic and recorded default times. We derive the probability distribution of these

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“…It is documented that these two notions of default do not necessarily coincide and the latter is typically later than the former (see Guo et al [8]). …”

Section: Remarkmentioning

confidence: 99%

Equilibrium model with default and dynamic insider information

2012

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We consider an equilibrium modelà la Kyle-Back for a defaultable claim issued by a given firm. In such a market the insider observes continuously in time the value of firm, which is unobservable by the market maker. Using the construction of a dynamic Bessel bridge of dimension 3 in [5], we provide the equilibrium price and the optimal insider's strategy. As in [3], the information released by the insider while trading optimally makes the default time predictable in market's view at the equilibrium. We conclude the paper by comparing the insider's expected profits in the static and dynamic private information case. We also compute explicitly the value of insider's information in the special cases of a defaultable stock and a bond.

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Distressed debt prices and recovery rate estimation

Cited by 25 publications

References 21 publications

Pricing CDOs with State Dependent Stochastic Recovery Rates

Pricing CDOs with State Dependent Stochastic Recovery Rates

On Modeling Economic Default Time: A Reduced-Form Model Approach

Equilibrium model with default and dynamic insider information

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