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

Schneider, Paul; Sögner, Leopold; Veža, Tanja

doi:10.1017/s0022109010000554

Cited by 59 publications

(33 citation statements)

References 69 publications

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“…Tests of the reduced-form models appear to be more successful (Duffee (1999), Driessen (2005), and Bakshi, Madan, and Zhang (2006)). Empirical studies of credit derivatives typically focus on reduced-form models (Houweling and Vorst (2005), Longstaff, Mithal, and Neis (2005), Chen, Cheng, Fabozzi, and Liu (2008), Schneider, Sögner, and Veza (2009)). 1 This is not very surprising, since these models are perceived as being flexible enough to be calibrated to arbitrary market data.…”

Section: Introductionmentioning

confidence: 99%

Does modeling framework matter? A comparative study of structural and reduced-form models

Gündüz

Uhrig‐Homburg

2013

Rev Deriv Res

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This study provides a rigorous empirical comparison of structural and reduced-form credit risk frameworks. As major difference we focus on the discriminative modeling of default time. In contrast to previous literature, we calibrate both approaches to bond and equity prices. By using same input data, applying comparable estimation techniques, and assessing the out-of-sample prediction quality on same time series of CDS prices we are able to judge whether empirically the model structure itself makes an important difference. Interestingly, the models' prediction power is quite close on average. Still, the reduced-form approach outperforms the structural for investment-grade names and longer maturities. JEL Classification: G13Keywords: Credit risk, structural models, reduced-form models, default intensity, stationary leverage, credit default swaps. Non-technical SummaryIn the financial industry, applying the Black/Scholes option pricing framework for pricing purposes has been widely accepted as the benchmark model for equity and FX derivatives.However, no single agreed pricing model has emerged that could serve as a benchmark for instruments that are exposed to credit risk. The literature differentiates between structural models that are based on modeling of the evolution of the balance sheet of the issuer, and reduced-form models that specify credit risk exogenously by a default intensity process.Until now, there has been no common agreement in academia and in the financial industry on which model framework better captures credit risk. In previous studies, even when testing the same model, the use of different datasets has contributed to quite different results. This study overcomes this issue by applying the same dataset to structural and reduced-form approaches. Leverage has been used as a key credit risk factor that could be explanatory in both frameworks. By using the same input data, applying comparable estimation techniques and assessing the out-of-sample prediction quality on the same time series of CDS prices, we are able to judge whether empirically the model structure itself makes an important difference. The models' predictive power is quite close on average, indicating that for pricing purposes the modeling type does not matter compared to the input data used. Still, the reduced-form approach outperforms the structural approach for investment-grade names and longer maturities. In contrast, the structural approach performs better for shorter maturities and sub-investment grade names. The study concludes that both frameworks provide CDS price prediction results equally well if a basis of comparison can be provided. These results have implications on choosing appropriate risk measurement techniques in financial markets.

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Section: Introductionmentioning

confidence: 99%

Does modeling framework matter? A comparative study of structural and reduced-form models

Gündüz

Uhrig‐Homburg

2013

Rev Deriv Res

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“…41 See for example, Schneider et al (2011). 42 Other papers analyzing this issue include Das and Hanouna (2006), Schlaefer and Uhrig-Homburg (2014), Conrad et al (2013), Doshi (2011), and Redouane Elkamhia and Pan (2014).…”

Section: Reduced-form Modelmentioning

confidence: 99%

Credit Default Swaps: A Survey

et al. 2014

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Credit default swaps (CDS) have been growing in importance in the global financial markets. However, their role has been hotly debated, in industry and academia, particularly after the credit crisis of 2008-2009 and the European sovereign crisis of 2010-2012. We review the extant literature on CDS that has accumulated over the past two decades. We divide our survey into seven topics after providing a broad overview in the introduction. The second section traces the historical development of CDS markets and provides an introduction to CDS contract definitions and conventions. The third section discusses the pricing of CDS, from the perspective of no-arbitrage principles as well as from that of structural and reduced-form credit risk models. It also summarizes the literature on the determinants of CDS spreads, with a focus on the role of fundamental credit risk factors, liquidity and counterparty risk. The fourth section discusses how the development of the CDS market has affected the characteristics of the related bond and equity markets, with an emphasis on the closely related concepts of market efficiency, price discovery, information flow and liquidity. Attention is also paid to the CDS-bond basis, the wedge between the pricing of the CDS and its reference bond, and the mispricing between the CDS and the equity market, which leads to a discussion on capital structure arbitrage. The fifth section examines the effect of CDS trading on firms' credit and bankruptcy risk, and how it affects corporate financial policy, including bond issuance, capital structure, liquidity management, and both external and internal corporate governance. The sixth section summarizes the literature that takes into account how CDS may impact the incentives of the various agents in the economy and the associated impact on the pricing of the contracts. In particular, we examine how CDS may alter the debtor-creditor relationship. Section seven reviews the growing literature on sovereign CDS and highlights the major conceptual and contractual differences between the sovereign and corporate CDS markets. In section eight, we discuss CDS indices, especially the role of synthetic CDS index products backed by residential mortgage-backed securities during the financial crisis. We close with our suggestions for promising future research directions on CDS contracts and markets.

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“…We utilize the dataset already used in Schneider et al (2010), where CDS spreads of 278 firms obtained from the Markit Group have been investigated. We focus on the five year maturities which are typically Using weekly data instead of daily observations is often done to avoid day of the week effects.…”

Section: Datamentioning

confidence: 99%

“…CDS Data: We use the CDS dataset already used in Schneider et al (2010), which was obtained from the Markit Group. After concentrating on the US market only and by excluding firms with a too large percentage of missing values, 278 firms had been used.…”

Section: Datamentioning

confidence: 99%

Parameter Estimation and Inference with Spatial Lags and Cointegration

Mutl

Sögner

2013

SSRN Journal

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We study dynamic panel data models where the long run outcome for a particular crosssection is affected by a weighted average of the outcomes in the other cross-sections. We show that imposing such a structure implies several cointegrating relationships that are nonlinear in the coefficients to be estimated. Assuming that the weights are exogenously given, we extend the dynamic ordinary least squares methodology and provide a dynamic two-stage least squares estimator. We derive the large sample properties of our proposed estimator and investigate its small sample distribution in a simulation study. Then our methodology is applied to US financial market data, which consist of credit default swap spreads, firm specific and industry data. A "closeness" measure for firms is based on inputoutput matrices. Our estimates show that this particular form of spatial correlation of credit default spreads is substantial and highly significant.

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

Cited by 59 publications

References 69 publications

Does modeling framework matter? A comparative study of structural and reduced-form models

Does modeling framework matter? A comparative study of structural and reduced-form models

Credit Default Swaps: A Survey

Parameter Estimation and Inference with Spatial Lags and Cointegration

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