Measuring Credit Risk of Individual Corporate Bonds in US Energy Sector

Takeaki Kariya (), Yoko Tanokura (), Hideyuki Takada () and Yoshiro Yamamura ()
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Takeaki Kariya: Josai International University
Yoko Tanokura: Meiji University
Hideyuki Takada: Toho University
Yoshiro Yamamura: Meiji University

Asia-Pacific Financial Markets, 2016, vol. 23, issue 3, No 1, 229-262

Abstract: Abstract In this paper, using the measures of the credit risk price spread (CRiPS) and the standardized credit risk price spread (S-CRiPS) proposed in Kariya’s (A CB (corporate bond) pricing model for deriving default probabilities and recovery rates. Eaton, IMS Collection Series: Festschrift for Professor Morris L., 2013) corporate bond model, we make a comprehensive empirical credit risk analysis on individual corporate bonds (CBs) in the US energy sector, where cross-sectional CB and government bond price data is used with bond attributes. Applying the principal component analysis method to the S-CRiPSs, we also categorize individual CBs into three different groups and study on their characteristics of S-CRiPS fluctuations of each group in association with bond attributes. Secondly, using the market credit rating scheme proposed by Kariya et al. (2014), we make credit-homogeneous groups of CBs and show that our rating scheme is empirically very timely and useful. Thirdly, we derive term structures of default probabilities for each homogeneous group, which reflect the investors’ views and perspectives on the future default probabilities or likelihoods implicitly implied by the CB prices for each credit-homogeneous group. Throughout this paper it is observed that our credit risk models and the associated measures for individual CBs work effectively and can timely provide the market credit information evaluated by investors.

Keywords: Credit risk price spread (CRiPS); Standardized credit risk price spread (S-CRiPS); Corporate bond; Term structure of default probabilities (TSDP); Market credit rating (M-Rating) (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10690-016-9217-7

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