IDEAS home Printed from https://ideas.repec.org/p/fip/fednrp/9711.html
   My bibliography  Save this paper

Split ratings and the pricing of credit risk

Author

Listed:
  • Richard Cantor
  • Kevin Cole
  • Frank Packer

Abstract

Despite the fact that over 50 percent of all corporate bonds have different ratings from Moody's and Standard and Poor's at issuance, most bond pricing models ignore these differences of opinion. Our work compares a number of different methods of accounting for split ratings in estimating bond pricing models. We find that pricing rules that use only the Moody's or Standard and Poor's ratings produce unbiased but highly inefficient forecasts. If models rely instead on simply the higher or lower of the two ratings (but not both), greater bias is introduced with insignificant gains in efficiency. In general, the average rating is the best guide to predicting yields in terms of both bias and forecast prediction. However, the forecasting advantage from using the average rating rather than the lower rating derives almost entirely from the below-investment-grade subsample.

Suggested Citation

  • Richard Cantor & Kevin Cole & Frank Packer, 1997. "Split ratings and the pricing of credit risk," Research Paper 9711, Federal Reserve Bank of New York.
  • Handle: RePEc:fip:fednrp:9711
    as

    Download full text from publisher

    File URL: https://www.newyorkfed.org/medialibrary/media/research/staff_reports/research_papers/9711.pdf
    Download Restriction: no

    File URL: https://www.newyorkfed.org/medialibrary/media/research/staff_reports/research_papers/9711.html
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Leland Crabbe, 1991. "Callable corporate bonds: a vanishing breed," Finance and Economics Discussion Series 155, Board of Governors of the Federal Reserve System (U.S.).
    2. Louis H. Ederington & Jess B. Yawitz & Brian E. Roberts, 1987. "The Informational Content Of Bond Ratings," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 10(3), pages 211-226, September.
    3. Larry G. Perry, 1985. "The Effect Of Bond Rating Agencies On Bond Rating Models," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 8(4), pages 307-315, December.
    4. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    5. Allen, David S & Lamy, Robert E & Thompson, G Rodney, 1990. "The Shelf Registration of Debt and Self Selection Bias," Journal of Finance, American Finance Association, vol. 45(1), pages 275-287, March.
    6. Thompson, G Rodney & Vaz, Peter, 1990. "Dual Bond Ratings: A Test of the Certification Function of Rating Agencies," The Financial Review, Eastern Finance Association, vol. 25(3), pages 457-471, August.
    7. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    8. Crabbe, Leland, 1991. "Event Risk: An Analysis of Losses to Bondholders and "Super Poison Put" Bond Covenants," Journal of Finance, American Finance Association, vol. 46(2), pages 689-706, June.
    9. Fabozzi, Frank J. & West, Richard R., 1981. "Negotiated versus Competitive Underwritings of Public Utility Bonds: Just One More Time," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 16(3), pages 323-339, September.
    10. Lamy, Robert E. & Thompson, G. Rodney, 1988. "Risk premia and the pricing of primary issue bonds," Journal of Banking & Finance, Elsevier, vol. 12(4), pages 585-601, December.
    11. Liu, Pu & Moore, William T, 1987. "The Impact of Split Bond Ratings on Risk Premia," The Financial Review, Eastern Finance Association, vol. 22(1), pages 71-85, February.
    12. Ma, Christopher K & Rao, Ramesh P & Peterson, Richard L, 1989. "The Resiliency of the High-Yield Bond Market: The LTV Default," Journal of Finance, American Finance Association, vol. 44(4), pages 1085-1097, September.
    Full references (including those not matched with items on IDEAS)

    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. Bae, Sung C. & Klein, Daniel P., 1997. "Further evidence on corporate bonds with event-risk covenants: Inferences from Standard and Poor's and Moody's bond ratings," The Quarterly Review of Economics and Finance, Elsevier, vol. 37(3), pages 709-724.
    2. Schaetzle, Dominik, 2011. "Ratingagenturen in der neoklassischen Finanzierungstheorie: Eine Auswertung empirischer Studien zum Informationsgehalt von Ratings," Arbeitspapiere 110, University of Münster, Institute for Cooperatives.
    3. de Albuquerquemello, Vinícius Phillipe & de Medeiros, Rennan Kertlly & da Nóbrega Besarria, Cássio & Maia, Sinézio Fernandes, 2018. "Forecasting crude oil price: Does exist an optimal econometric model?," Energy, Elsevier, vol. 155(C), pages 578-591.
    4. Sucarrat, Genaro, 2009. "Forecast Evaluation of Explanatory Models of Financial Variability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-33.
    5. Kish, Richard J. & Hogan, Karen M. & Olson, Gerard, 1999. "Does the market perceive a difference in rating agencies?," The Quarterly Review of Economics and Finance, Elsevier, vol. 39(3), pages 363-377.
    6. Hamid Baghestani, 2010. "Evaluating Blue Chip forecasts of the trade-weighted dollar exchange rate," Applied Financial Economics, Taylor & Francis Journals, vol. 20(24), pages 1879-1889.
    7. West, Kenneth D & McCracken, Michael W, 1998. "Regression-Based Tests of Predictive Ability," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 817-840, November.
    8. Heather L. R. Tierney, 2019. "Forecasting with the Nonparametric Exclusion-from-Core Inflation Persistence Model Using Real-Time Data," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 25(1), pages 39-63, February.
    9. Edward M. Werner, 2011. "The value relevance of pension accounting information: evidence fromFortune200 firms," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 10(4), pages 427-458, November.
    10. Datta, Sudip & Iskandar-Datta, Mai & Raman, Kartik, 2000. "Debt Structure Adjustments and Long-Run Stock Price Performance," Journal of Financial Intermediation, Elsevier, vol. 9(4), pages 427-453, October.
    11. Angelidis, Timotheos & Benos, Alexandros & Degiannakis, Stavros, 2004. "The Use of GARCH Models in VaR Estimation," MPRA Paper 96332, University Library of Munich, Germany.
    12. King, Tao-Hsien Dolly, 2007. "Are embedded calls valuable? Evidence from agency bonds," Journal of Banking & Finance, Elsevier, vol. 31(1), pages 57-79, January.
    13. Nii Ayi Armah & Norman Swanson, 2010. "Seeing Inside the Black Box: Using Diffusion Index Methodology to Construct Factor Proxies in Large Scale Macroeconomic Time Series Environments," Econometric Reviews, Taylor & Francis Journals, vol. 29(5-6), pages 476-510.
    14. Hang Luo & Linfeng Chen, 2019. "Bond yield and credit rating: evidence of Chinese local government financing vehicles," Review of Quantitative Finance and Accounting, Springer, vol. 52(3), pages 737-758, April.
    15. Fayez Elayan & Wei Hsu & Thomas Meyer, 2003. "The informational content of credit rating announcements for share prices in a small market," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 27(3), pages 337-356, September.
    16. Antonakakis, Nikolaos & Darby, Julia, 2012. "Forecasting Volatility in Developing Countries' Nominal Exchange Returns," MPRA Paper 40875, University Library of Munich, Germany.
    17. Rapach, David E. & Wohar, Mark E., 2002. "Testing the monetary model of exchange rate determination: new evidence from a century of data," Journal of International Economics, Elsevier, vol. 58(2), pages 359-385, December.
    18. Massimiliano Marcellino, "undated". "Further Results on MSFE Encompassing," Working Papers 143, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    19. Arie Melnik & Doron Nissim, 2003. "Debt issue costs and issue characteristics in the Eurobond market," ICER Working Papers 09-2003, ICER - International Centre for Economic Research.
    20. Tierney, Heather L.R., 2011. "Forecasting and tracking real-time data revisions in inflation persistence," MPRA Paper 34439, University Library of Munich, Germany.

    More about this item

    Keywords

    Bonds; Credit; Risk;
    All these keywords.

    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:fip:fednrp:9711. 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: Gabriella Bucciarelli (email available below). General contact details of provider: https://edirc.repec.org/data/frbnyus.html .

    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.