Is Credit Event Risk Priced? Modeling Contagion via the Updating of Beliefs.

Collin‐Dufresne, Pierre; Goldstein, Robert S.; Helwege, Jean

doi:10.3386/w15733

Cited by 143 publications

(95 citation statements)

References 49 publications

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“…Such setups arise, e.g., in the presence of counterparty risk (as in Kusuoka (1999) and Jarrow and Yu (2001)) or contagion (as in Collin-Dufresne, Goldstein, and Helwege (2003)). …”

Section: Default Risk Premiamentioning

confidence: 99%

“…20 Cases in which the doubly stochastic setting no longer holds are studied in Duffie, Schroder, and Skiadas (1996), Kusuoka (1999), Jarrow and Yu (2001), Collin-Dufresne, Goldstein, and Helwege (2003) and to the assumption inherent in the Cox process setup that the filtration generated by the default components is conditionally independent of the default event, there do not exist feedback effects from the default time into the default components to be considered in the valuation.…”

Section: Default Risk Premiamentioning

confidence: 99%

See 1 more Smart Citation

The Economic Role of Jumps and Recovery Rates in the Market for Corporate Default Risk

Schneider¹,

Sögner²,

Veža³

2010

J. Financ. Quant. Anal.

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A previous version of this paper was circulated as "Jumps and Recovery Rates Inferred from Corporate CDS Premia". We are thankful to FIRM@WU for access to their high-performance computing resources as well as friendly support, and to Dow Jones for providing us with complete ICB sector information. AbstractUsing an extensive cross-section of US corporate CDS this paper offers an economic understanding of implied loss given default (LGD) and jumps in default risk. We formulate and underpin empirical stylized facts about CDS spreads, which are then reproduced in our affine intensity-based jump-diffusion model. Implied LGD is well identified, with obligors possessing substantial tangible assets expected to recover more. Sudden increases in the default risk of investment-grade obligors are higher relative to speculative grade. The probability of structural migration to default is low for investment-grade and heavily regulated obligors because investors fear distress rather through rare but devastating events.

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“…Such setups arise, e.g., in the presence of counterparty risk (as in Kusuoka (1999) and Jarrow and Yu (2001)) or contagion (as in Collin-Dufresne, Goldstein, and Helwege (2003)). …”

Section: Default Risk Premiamentioning

confidence: 99%

Section: Default Risk Premiamentioning

confidence: 99%

The Economic Role of Jumps and Recovery Rates in the Market for Corporate Default Risk

Schneider¹,

Sögner²,

Veža³

2010

J. Financ. Quant. Anal.

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show abstract

“…Jorion and Zhang (2007) conduct a larger scale analysis over bankruptcies and find similar results. The reason for these seemingly unrelated firms sharing a default factor can be learning, as argued by Collin-Dufresne, Goldstein, and Helwege (2003) and Giesecke (2004) or market structure as argued by Allen and Carletti (2006).…”

Section: Frailty Correlated Default Model and Simulation Methodsmentioning

confidence: 99%

A Little Knowledge Is a Dangerous Thing: Model Specification, Data History, and CDO (Mis)Pricing

Luo

Wang

Tang³

2009

SSRN Journal

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The revaluation of collateralized debt obligations (CDOs) plays a significant role in the ongoing 2007-2009 credit crisis. Starting in August 2007, a large amount of initially AAA rated CDO securities are substantially downgraded, some directly to junk grade. This paper explores two structural sources of CDO mispricing: modeling difficulty and data limitation. Simulating the frailty correlated default model of Duffie, Eckner, Horel, and Saita (2008), we show that CDO mis-pricing can be partly attributed to model misspecifications, as well as limited availability of historical data on CDO collateral assets. This simulation result is consistent with empirical evidence on historical performance of a sample of 279 CDOs. The frailty model estimated with adequate historical data would have reduced the amount of AAA rated CDO securities by 12% on average. The frailty model has predictive power for the subsequent downgrading of AAA rated CDO tranches. Our study addresses practical issues on financial innovations and provides guidance for corresponding risk management. * , a large amount of initially AAA rated CDO securities are substantially downgraded, some directly to junk grade. This paper explores two structural sources of CDO mispricing: modeling difficulty and data limitation. Simulating the frailty correlated default model of Duffie, Eckner, Horel, and Saita (2008), we show that CDO mis-pricing can be partly attributed to model misspecifications, as well as limited availability of historical data on CDO collateral assets. This simulation result is consistent with empirical evidence on historical performance of a sample of 279 CDOs. The frailty model estimated with adequate historical data would have reduced the amount of AAA rated CDO securities by 12% on average. The frailty model has predictive power for the subsequent downgrading of AAA rated CDO tranches. Our study addresses practical issues on financial innovations and provides guidance for corresponding risk management.

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“…Kusuoka (1999), Duffie & Lando (2001), Giesecke (2004), Jarrow & Protter (2004), Giesecke (2004), Coculescu, Geman, & Jeanblanc (2008) and Frey & Schmidt (2006) are concerned with structural models where the value of assets and/or liabilities is not directly observable. Reduced form credit risk models with incomplete information such as our paper have been considered by Schönbucher (2004), Collin-Dufresne, Goldstein & Helwege (2003) and Duffie, Eckner, Horel & Saita (2006). The structure of the latter three models is relatively similar: default intensities are driven by an unobservable factor (process) X; given information about X, the default times are conditionally independent, doubly stochastic random times; finally, the investor information (F I t ) is given by the default history of the portfolio, augmented by economic covariates.…”

Section: Introductionmentioning

confidence: 99%

Pricing credit derivatives under incomplete information: a nonlinear-filtering approach

Frey

Runggaldier

2010

Finance Stoch

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This paper considers a general reduced form pricing model for credit derivatives where default intensities are driven by some factor process X. The process X is not directly observable for investors in secondary markets; rather, their information set consists of the default history and of noisy price observation for traded credit products. In this context the pricing of credit derivatives leads to a challenging nonlinear filtering problem. We provide recursive updating rules for the filter, derive a finite dimensional filter for the case where X follows a finite state Markov chain and propose a novel particle filtering algorithm. A numerical case study illustrates the properties of the proposed algorithms.

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Is Credit Event Risk Priced? Modeling Contagion via the Updating of Beliefs.

Cited by 143 publications

References 49 publications

The Economic Role of Jumps and Recovery Rates in the Market for Corporate Default Risk

The Economic Role of Jumps and Recovery Rates in the Market for Corporate Default Risk

A Little Knowledge Is a Dangerous Thing: Model Specification, Data History, and CDO (Mis)Pricing

Pricing credit derivatives under incomplete information: a nonlinear-filtering approach

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