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Split ratings and the pricing of credit risk

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  • 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
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    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. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    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.
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    Keywords

    Bonds; Credit; Risk;
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