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Predicting credit spreads

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  • Krishnan, C.N.V.
  • Ritchken, Peter H.
  • Thomson, James B.

Abstract

Predictions of firm-level credit spreads based on the current spot and forward credit spreads can be significantly improved upon by using the information contained in the shape of the credit-spread curve. However, the current credit-spread curve is not a sufficient statistic for predicting future out-of-sample credit spreads; predictions can be significantly improved upon by exploiting the information contained in the shape of the riskless yield curve. In the presence of credit-spread and riskless factors, other macroeconomic, marketwide, and firm-specific risk variables do not significantly improve predictions of credit spreads. These results have important implications for credit-spreads modeling as well as for better understanding corporate capital structure and risk management policies.

Suggested Citation

  • Krishnan, C.N.V. & Ritchken, Peter H. & Thomson, James B., 2010. "Predicting credit spreads," Journal of Financial Intermediation, Elsevier, vol. 19(4), pages 529-563, October.
    • Handle: RePEc:eee:jfinin:v:19:y:2010:i:4:p:529-563
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    2. Thiago De Oliveira Souza, 2011. "Forecasting Investment-Grade Credit-Spreads. A Regularized Approach," Working Papers ECARES ECARES 2011-037, ULB -- Universite Libre de Bruxelles.
    3. Audzeyeva, Alena & Fuertes, Ana-Maria, 2018. "On the predictability of emerging market sovereign credit spreads," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 140-157.
    4. Comelli, Fabio, 2012. "Emerging market sovereign bond spreads: Estimation and back-testing," Emerging Markets Review, Elsevier, vol. 13(4), pages 598-625.
    5. Xiu Xu & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle, 2019. "Dynamic credit default swap curves in a network topology," Quantitative Finance, Taylor & Francis Journals, vol. 19(10), pages 1705-1726, October.
    6. Saker Sabkha & Christian de Peretti & Dorra Hmaied, 2018. "Forecasting sovereign CDS volatility: A comparison of univariate GARCH-class models," Working Papers hal-01769390, HAL.
    7. Kalimipalli, Madhu & Nayak, Subhankar & Perez, M. Fabricio, 2013. "Dynamic effects of idiosyncratic volatility and liquidity on corporate bond spreads," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 2969-2990.
    8. Takeshi Kobayashi, 2021. "Common Factors in the Term Structure of Credit Spreads and Predicting the Macroeconomy in Japan," IJFS, MDPI, vol. 9(2), pages 1-12, April.
    9. Saeed, Momna & Elnahass, Marwa & Izzeldin, Marwan & Tsionas, Mike, 2021. "Yield spread determinants of sukuk and conventional bonds," Economic Modelling, Elsevier, vol. 105(C).
    10. Vijay A. Murik, 2013. "Bond pricing with a surface of zero coupon yields," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 53(2), pages 497-512, June.
    11. Shaw, Frances & Murphy, Finbarr & O’Brien, Fergal, 2014. "The forecasting efficiency of the dynamic Nelson Siegel model on credit default swaps," Research in International Business and Finance, Elsevier, vol. 30(C), pages 348-368.
    12. Saker Sabkha, 2021. "Forecasting sovereign CDS volatility: A comparison of univariate GARCH-class models," Post-Print hal-01769390, HAL.

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