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.

Autorentext
Dr. Timo Schläfer completed his doctoral thesis under the supervision of Prof. Dr. Marliese Uhrig-Homburg at the Chair of Financial Engineering and Derivatives at the Karlsruhe Institute of Technology. He works in the investment banking industry.

Zusammenfassung
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.

Inhalt
Recovery Rates under the Physical Probability Measure; Prior Research on the Estimation of Implied Recovery Rates; Loan-Only Credit Default Swaps; A Default-Free Metric of Implied Recovery Rates; The Properties of Implied Recovery Rates; Risk Aversion in Implied Default and Recovery Rates