IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v3y2006i2p79-95.html
   My bibliography  Save this article

From default probabilities to credit spreads: Credit risk models do explain market prices

Author

Listed:
  • Denzler, Stefan M.
  • Dacorogna, Michel M.
  • Muller, Ulrich A.
  • McNeil, Alexander J.

Abstract

Credit risk models like Moody’s 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 Moody’s 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.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Denzler, Stefan M. & Dacorogna, Michel M. & Muller, Ulrich A. & McNeil, Alexander J., 2006. "From default probabilities to credit spreads: Credit risk models do explain market prices," Finance Research Letters, Elsevier, vol. 3(2), pages 79-95, June.
  • Handle: RePEc:eee:finlet:v:3:y:2006:i:2:p:79-95
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544-6123(06)00004-3
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Michel Dacorogna & Gianluca Oderda & Tobias Jung, 2003. "Credit Risk Models - Do They Deliver Their Promises? A Quantitative Assessment," Risk and Insurance 0306003, University Library of Munich, Germany.
    2. 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.
    3. 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 449-470, May.
    4. 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.
    5. Delianedis, Gordon & Geske, Robert, 1998. "Credit Risk and Risk Neutral Default Probabilities: Information About Migrations and Defaults," University of California at Los Angeles, Anderson Graduate School of Management qt7dm2d31p, Anderson Graduate School of Management, UCLA.
    6. Gençay, Ramazan & Dacorogna, Michel & Muller, Ulrich A. & Pictet, Olivier & Olsen, Richard, 2001. "An Introduction to High-Frequency Finance," Elsevier Monographs, Elsevier, edition 1, number 9780122796715.
    7. 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, July.
    8. Jon Frye, 2000. "Depressing recoveries," Emerging Issues, Federal Reserve Bank of Chicago, issue Oct.
    9. Acharya, Viral & Bharath, Sreedhar T & Srinivasan, Anand, 2003. "Understanding the Recovery Rates on Defaulted Securities," CEPR Discussion Papers 4098, C.E.P.R. Discussion Papers.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. John A. Major, 2019. "Methodological Considerations in the Statistical Modeling of Catastrophe Bond Prices," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 22(1), pages 39-56, March.
    2. Mirza, Nawazish & Rahat, Birjees & Naqvi, Bushra & Rizvi, Syed Kumail Abbas, 2023. "Impact of Covid-19 on corporate solvency and possible policy responses in the EU," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 181-190.
    3. Andreasen, Eugenia & Valenzuela, Patricio, 2016. "Financial openness, domestic financial development and credit ratings," Finance Research Letters, Elsevier, vol. 16(C), pages 11-18.
    4. P. Zhukov E. & П. Жуков Е., 2018. "Разве стоимость компании действительно зависит от средневзвешенной стоимости капитала и свободного денежного потока? Свидетельства иррациональности в нефтегазовом секторе // Does Enterprise Value Real," Review of Business and Economics Studies // Review of Business and Economics Studies, Финансовый Университет // Financial University, vol. 6(1), pages 17-28.
    5. Khan, Mohammad Azeem & Ahmad, Wasim, 2022. "Fresh evidence on the relationship between market power and default risk of Indian banks," Finance Research Letters, Elsevier, vol. 46(PA).
    6. Mitra, Sovan & Karathanasopoulos, Andreas & Sermpinis, Georgios & Dunis, Christian & Hood, John, 2015. "Operational risk: Emerging markets, sectors and measurement," European Journal of Operational Research, Elsevier, vol. 241(1), pages 122-132.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Maclachlan, Iain C, 2007. "An empirical study of corporate bond pricing with unobserved capital structure dynamics," MPRA Paper 28416, University Library of Munich, Germany.
    2. J. B. Glattfelder & A. Dupuis & R. B. Olsen, 2010. "Patterns in high-frequency FX data: discovery of 12 empirical scaling laws," Quantitative Finance, Taylor & Francis Journals, vol. 11(4), pages 599-614.
    3. Baldovin, Fulvio & Caporin, Massimiliano & Caraglio, Michele & Stella, Attilio L. & Zamparo, Marco, 2015. "Option pricing with non-Gaussian scaling and infinite-state switching volatility," Journal of Econometrics, Elsevier, vol. 187(2), pages 486-497.
    4. Manish K. Singh & Marta Gómez-Puig & Simón Sosvilla-Rivero, 2014. "Forward looking banking stress in EMU countries," Working Papers 14-10, Asociación Española de Economía y Finanzas Internacionales.
    5. Noemi Nava & T. Di Matteo & Tomaso Aste, 2015. "Anomalous volatility scaling in high frequency financial data," Papers 1503.08465, arXiv.org, revised Dec 2015.
    6. Agarwal, Vineet & Taffler, Richard, 2008. "Comparing the performance of market-based and accounting-based bankruptcy prediction models," Journal of Banking & Finance, Elsevier, vol. 32(8), pages 1541-1551, August.
    7. Aggarwal, Nidhi & Singh, Manish K. & Thomas, Susan, 2023. "Do decreases in Distance-to-Default predict rating downgrades?," Economic Modelling, Elsevier, vol. 129(C).
    8. Li, Ming-Yuan Leon & Miu, Peter, 2010. "A hybrid bankruptcy prediction model with dynamic loadings on accounting-ratio-based and market-based information: A binary quantile regression approach," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 818-833, September.
    9. Li-Su Huang, 2022. "Directors and officers liability insurance and default risk," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(2), pages 375-408, April.
    10. Nava, Noemi & Di Matteo, T. & Aste, Tomaso, 2016. "Anomalous volatility scaling in high frequency financial data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 434-445.
    11. Barunik, Jozef & Aste, Tomaso & Di Matteo, T. & Liu, Ruipeng, 2012. "Understanding the source of multifractality in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4234-4251.
    12. Nidhi Aggarwal & Manish K. Singh & Susan Thomas, 2022. "Informational efficiency of credit ratings," Working Papers 14, xKDR.
    13. Marta Gómez-Puig & Simón Sosvilla-Rivero & Manish K. Singh, 2018. "“Incorporating creditors' seniority into contingent claim models:Application to peripheral euro area countries”," IREA Working Papers 201803, University of Barcelona, Research Institute of Applied Economics, revised Feb 2018.
    14. Wesselhöfft, Niels & Härdle, Wolfgang Karl, 2019. "Estimating low sampling frequency risk measure by high-frequency data," IRTG 1792 Discussion Papers 2019-003, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    15. Wei Ting & Sin‐Hui Yen & Chien‐Liang Chiu, 2008. "The Influence of Qualified Foreign Institutional Investors on the Association between Default Risk and Audit Opinions: Evidence from the Chinese Stock Market," Corporate Governance: An International Review, Wiley Blackwell, vol. 16(5), pages 400-415, September.
    16. Annalisa Di Clemente, 2013. "Considering the dependence between the credit loss severity and the probability of default in the estimate of portfolio credit risk: an experimental analysis," STUDI ECONOMICI, FrancoAngeli Editore, vol. 2013(109), pages 5-24.
    17. Singh, Manish K. & Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2015. "Bank risk behavior and connectedness in EMU countries," Journal of International Money and Finance, Elsevier, vol. 57(C), pages 161-184.
    18. Jayasekera, Ranadeva, 2018. "Prediction of company failure: Past, present and promising directions for the future," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 196-208.
    19. Pesaran, M. Hashem & Schuermann, Til & Treutler, Bjorn-Jakob & Weiner, Scott M., 2006. "Macroeconomic Dynamics and Credit Risk: A Global Perspective," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1211-1261, August.
    20. Lallouache, Mehdi & Abergel, Frédéric, 2014. "Tick size reduction and price clustering in a FX order book," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 488-498.

    More about this item

    JEL classification:

    • 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; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:3:y:2006:i:2:p:79-95. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.