Recovery Risk in Credit Default Swap Premia [electronic resource] /
Schläfer, Timo.author.
The finance literature looks at a number of factors to explain risk premia in corporate debt, such as liquidity effects, jump-to-default risk, and contagion risk. Stochastic recovery rates as a source of systematic risk have not received much attention so far, most likely due to the difficulties around decomposing the expected loss. Timo Schläfer exploits the fact that differently-ranking debt instruments of the same issuer face identical default risk but different default-conditional recovery rates. He shows that this allows isolating recovery risk without any of the rigid assumptions employed by priors and implements his approach using credit default swap data.
Description based upon print version of record.
Preface; Table of Contents; List of Figures; List of Tables; List of Abbreviations; List of Symbols; 1 Introduction; 2 Related Literature; 2.1 Characteristics of Physical Recovery Rates; 2.2 On the Estimation of Implied Recovery Rates; 2.2.1 The Identification Problem; 2.2.2 A Review of Earlier Studies; 3 A New Approach to Estimating Market-Implied Recovery Rates; 3.1 A Default-Free Metric of Implied Recovery; 3.2 The Link to Capital Structure; 3.3 The Implied Probability Distribution of Recovery; 4 A Review of Appropriable Credit Derivatives; 4.1 Credit Default Swaps on Corporate Debt
4.2 Leveraged Loans and Bonds4.2.1 Origination, Information, and Transferability; 4.2.2 The Structure of Leveraged Loans; 4.2.3 Collateral and Covenants; 4.2.4 Coupons and Prepayment; 4.3 Standard Terms of Single-Name Credit Default Swaps; 4.3.1 Framework Documentation; 4.3.2 Investors' Requirements; 4.3.3 Reference Entity and Reference Obligation; 4.3.4 Contract Cancellation; 4.3.5 Credit Events; 4.4 Key Topics Revisited; 5 Implementation and Results; 5.1 Data and Descriptive Statistics; 5.1.1 Construction of Samples; 5.1.2 Credit Default Swap Premia; 5.1.3 Capital Structure Data
5.2 Empirical Specification5.2.1 The Ratio of Premia; 5.2.2 Linking the Implied Distribution to Economic Factors; 5.2.3 Calibration Results; 5.3 Estimation Results of Market-Implied Recovery Rates; 5.3.1 Implied Firm-Wide and Instrument-Specific Recovery Rates; 5.3.2 The Impact of Debt Cushion; 5.3.3 The Impact of Changes in the Economic Environment; 5.3.4 The Relation to Ratings; 5.4 Robustness; 5.4.1 Alternative Parameterization; 5.4.2 Sample-Specific Calibration; 5.4.3 Risk Aversion in Implied Recovery Rates; 5.5 Application: Deducing the Implied Probability of Default
5.5.1 A Simplistic Approach5.5.2 The Relation to Implied Expected Recovery Rates; 5.5.3 Risk Aversion in the Implied Probability of Default; 6 Conclusion and Outlook; Appendices; A Supremum and Infimum Standard Deviations; A.I Beta Distribution; A.II Transformed Normal Distribution; A.III Quadratic Distribution; B Descriptive Statistics by Firm; C The Variance of Implied Expected Recovery Rates; D Implied Recovery Rates by Firm; E Implied Recovery Rates by Firm - Sample-Specific Calibration; F Implied One-Year Probabilities of Default by Firm; References
Dissertation Karlsruhe Institute of Technology, 2010.
Includes bibliographical references.
The finance literature looks at a number of factors to explain risk premia in corporate debt, such as liquidity effects, jump-to-default risk, and contagion risk. Stochastic recovery rates as a source of systematic risk have not received much attention so far, most likely due to the difficulties around decomposing the expected loss. Timo Schläfer exploits the fact that differently-ranking debt instruments of the same issuer face identical default risk but different default-conditional recovery rates. He shows that this allows isolating recovery risk without any of the rigid assumptions employed by priors and implements his approach using credit default swap data.
Finance.
Operations research.
Decision making.
Finance, general.
Operations Research/Decision Theory.