From default probabilities to credit spreads: Credit risk models do explain market prices
AbstractCredit risk models like Moodyâs KMV are now well established in the market and give bond managers reliable estimates of default probabilities for individual firms. Until now it has been hard to relate those probabilities to the actual credit spreads observed on the market for corporate bonds. Inspired by the existence of scaling laws in financial markets by Dacorogna et al. (2001) and Di Matteo et al. (2005) deviating from the Gaussian behavior, we develop a model that quantitatively links those default probabilities to credit spreads (market prices). The main input quantities to this study are merely industry yield data of different times to maturity and expected default frequencies (EDFs) of Moodyâs KMV. The empirical results of this paper clearly indicate that the model can be used to calculate approximate credit spreads (market prices) from EDFs, independent of the time to maturity and the industry sector under consideration. Moreover, the model is effective in an out-of-sample setting, it produces consistent results on the European bond market where data are scarce and can be adequately used to approximate credit spreads on the corporate level.
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Bibliographic InfoArticle provided by Elsevier in its journal Finance Research Letters.
Volume (Year): 3 (2006)
Issue (Month): 2 (June)
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Web page: http://www.elsevier.com/locate/frl
Other versions of this item:
- Stefan Denzler & Michel M. Dacorogna & Ulrich A. Mueller & Alexander McNeil, 2005. "From Default Probabilities To Credit Spreads: Credit Risk Models Do Explain Market Prices," Finance 0504011, EconWPA.
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing
- G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Merton, Robert C, 1974.
"On the Pricing of Corporate Debt: The Risk Structure of Interest Rates,"
Journal of Finance,
American Finance Association, vol. 29(2), pages 449-70, May.
- Merton, Robert C., 1973. "On the pricing of corporate debt: the risk structure of interest rates," Working papers 684-73., Massachusetts Institute of Technology (MIT), Sloan School of Management.
- Michel Dacorogna & Gianluca Oderda & Tobias Jung, 2003.
"Credit Risk Models - Do They Deliver Their Promises? A Quantitative Assessment,"
Risk and Insurance
- Gianluca Oderda & Michel M. Dacorogna & Tobias Jung, 2003. "Credit Risk Models - Do They Deliver Their Promises? A Quantitative Assessment," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 32(2), pages 177-195, 07.
- T. Di Matteo & T. Aste & M. M. Dacorogna, 2004.
"Long term memories of developed and emerging markets: using the scaling analysis to characterize their stage of development,"
- Matteo, T. Di & Aste, T. & Dacorogna, Michel M., 2005. "Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 827-851, April.
- T. Di Matteo & T. Aste & Michel M. Dacorogna, 2005. "Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development," Econometrics 0503004, EconWPA.
- Muller, Ulrich A. & Dacorogna, Michel M. & Olsen, Richard B. & Pictet, Olivier V. & Schwarz, Matthias & Morgenegg, Claude, 1990. "Statistical study of foreign exchange rates, empirical evidence of a price change scaling law, and intraday analysis," Journal of Banking & Finance, Elsevier, vol. 14(6), pages 1189-1208, December.
- Jon Frye, 2000. "Depressing recoveries," Emerging Issues, Federal Reserve Bank of Chicago, issue Oct.
- Acharya, Viral V & Bharath, Sreedhar T & Srinivasan, Anand, 2003. "Understanding the Recovery Rates on Defaulted Securities," CEPR Discussion Papers 4098, C.E.P.R. Discussion Papers.
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