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Can rating agencies look through the cycle?

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  • Gunter Löffler

Abstract

Rating agencies claim to look through the cycle when assigning corporate credit ratings, which entails that they are able to separate trend components of default risk from transitory ones. To test whether agencies possess this competence, I take market-based estimates of 1-year default probabilities of corporate bond issuers and estimate their long-run trend using the Hodrick-Prescott filter, local regression, or centered moving averages. I find that ratings help identify the current split into trend and cycle. In addition, rating stability is similar to the one of hypothetical ratings based on long-term trends. The results are robust to the use of different filter techniques. They are confirmed by a model-free analysis, which shows that ratings predict future changes in market-based default probability estimates. Since the examined trends are forward-looking in the sense that the trend filtering algorithms use future data, agency ratings exhibit important characteristics one would expect from ratings that see through the cycle. Copyright Springer Science+Business Media, LLC 2013

Suggested Citation

  • Gunter Löffler, 2013. "Can rating agencies look through the cycle?," Review of Quantitative Finance and Accounting, Springer, vol. 40(4), pages 623-646, May.
    • Handle: RePEc:kap:rqfnac:v:40:y:2013:i:4:p:623-646
    DOI: 10.1007/s11156-012-0289-9
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    1. Stohs, Mark Hoven & Mauer, David C, 1996. "The Determinants of Corporate Debt Maturity Structure," The Journal of Business, University of Chicago Press, vol. 69(3), pages 279-312, July.
    2. Jan-Henning Trustorff & Paul Konrad & Jens Leker, 2011. "Credit risk prediction using support vector machines," Review of Quantitative Finance and Accounting, Springer, vol. 36(4), pages 565-581, May.
    3. H. Kent Baker & Sattar A. Mansi, 2002. "Assessing Credit Rating Agencies by Bond Issuers and Institutional Investors," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 29(9&10), pages 1367-1398.
    4. Geske, Robert & Johnson, H. E., 1984. "The Valuation of Corporate Liabilities as Compound Options: A Correction," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 19(2), pages 231-232, June.
    5. John Y. Campbell & Martin Lettau & Burton G. Malkiel & Yexiao Xu, 2001. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," Journal of Finance, American Finance Association, vol. 56(1), pages 1-43, February.
    6. Nickell, Pamela & Perraudin, William & Varotto, Simone, 2000. "Stability of rating transitions," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 203-227, January.
    7. Eugene F. Fama, 2002. "Testing Trade-Off and Pecking Order Predictions About Dividends and Debt," The Review of Financial Studies, Society for Financial Studies, vol. 15(1), pages 1-33, March.
    8. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    9. Flannery, Mark J. & Rangan, Kasturi P., 2006. "Partial adjustment toward target capital structures," Journal of Financial Economics, Elsevier, vol. 79(3), pages 469-506, March.
    10. Lili Sun, 2007. "A re-evaluation of auditors’ opinions versus statistical models in bankruptcy prediction," Review of Quantitative Finance and Accounting, Springer, vol. 28(1), pages 55-78, January.
    11. Mark Meyer & Peter Winker*, 2005. "Using HP Filtered Data for Econometric Analysis: Some Evidence from Monte Carlo Simulations," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 89(3), pages 303-320, August.
    12. Regina Kaiser & Agustín Maravall, 1999. "Estimation of the business cycle: A modified Hodrick-Prescott filter," Spanish Economic Review, Springer;Spanish Economic Association, vol. 1(2), pages 175-206.
    13. Mitchell A. Petersen, 2009. "Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches," The Review of Financial Studies, Society for Financial Studies, vol. 22(1), pages 435-480, January.
    14. Carey, Mark & Hrycay, Mark, 2001. "Parameterizing credit risk models with rating data," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 197-270, January.
    15. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-247, July-Sept.
    16. Amato, Jeffery D. & Furfine, Craig H., 2004. "Are credit ratings procyclical?," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2641-2677, November.
    17. 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.
    18. Graham, John R. & Harvey, Campbell R., 2001. "The theory and practice of corporate finance: evidence from the field," Journal of Financial Economics, Elsevier, vol. 60(2-3), pages 187-243, May.
    19. Leland, Hayne E & Toft, Klaus Bjerre, 1996. "Optimal Capital Structure, Endogenous Bankruptcy, and the Term Structure of Credit Spreads," Journal of Finance, American Finance Association, vol. 51(3), pages 987-1019, July.
    20. Pedersen, Torben Mark, 2001. "The Hodrick-Prescott filter, the Slutzky effect, and the distortionary effect of filters," Journal of Economic Dynamics and Control, Elsevier, vol. 25(8), pages 1081-1101, August.
    21. Bangia, Anil & Diebold, Francis X. & Kronimus, Andre & Schagen, Christian & Schuermann, Til, 2002. "Ratings migration and the business cycle, with application to credit portfolio stress testing," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 445-474, March.
    22. Warga, Arthur & Welch, Ivo, 1993. "Bondholder Losses in Leveraged Buyouts," The Review of Financial Studies, Society for Financial Studies, vol. 6(4), pages 959-982.
    23. Darren J. Kisgen, 2006. "Credit Ratings and Capital Structure," Journal of Finance, American Finance Association, vol. 61(3), pages 1035-1072, June.
    24. Geske, Robert, 1977. "The Valuation of Corporate Liabilities as Compound Options," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 12(4), pages 541-552, November.
    25. Ehlgen, Jurgen, 1998. "Distortionary effects of the optimal Hodrick-Prescott filter," Economics Letters, Elsevier, vol. 61(3), pages 345-349, December.
    26. Giovanni Butera & Robert Faff, 2006. "An integrated multi-model credit rating system for private firms," Review of Quantitative Finance and Accounting, Springer, vol. 27(3), pages 311-340, November.
    27. Cantor, Richard, 2001. "Moody's investors service response to the consultative paper issued by the Basel Committee on Bank Supervision "A new capital adequacy framework"," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 171-185, January.
    28. King, Robert G. & Rebelo, Sergio T., 1993. "Low frequency filtering and real business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 207-231.
    29. Altman, Edward I. & Rijken, Herbert A., 2004. "How rating agencies achieve rating stability," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2679-2714, November.
    30. H. Kent Baker & Sattar A. Mansi, 2002. "Assessing Credit Rating Agencies by Bond Issuers and Institutional Investors," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 29(9‐10), pages 1367-1398.
    31. Cogley, Timothy & Nason, James M., 1995. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series Implications for business cycle research," Journal of Economic Dynamics and Control, Elsevier, vol. 19(1-2), pages 253-278.
    32. Sreedhar T. Bharath & Tyler Shumway, 2008. "Forecasting Default with the Merton Distance to Default Model," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1339-1369, May.
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    2. Mingzhi Liu & Michel Magnan, 2016. "Conditional conservatism and the yield spread of corporate bond issues," Review of Quantitative Finance and Accounting, Springer, vol. 46(4), pages 847-879, May.

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    More about this item

    Keywords

    Default risk; Credit ratings; Through-the-cycle; Hodrick-Prescott filter; Merton model; G20; G33;
    All these keywords.

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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