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Discovering the impact of systemic and idiosyncratic risk factors on credit spread of corporate bond within the framework of intelligent knowledge management

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Abstract

This paper exploits the implied information of data collected from credit spreads of Chinese corporate bonds and systemic and idiosyncratic risk factors. We compute contribution of risk factors to credit spreads of Chinese corporate bonds by establishing the unbalanced panel data model, identify the key factors impacting the size of credit spreads of corporate bonds. Knowledge extracted by data mining is helpful to investors for reasonable pricing of bonds and making rational investment decisions. When selecting variables, the unbalanced panel data model is used to calculate the Zero-volatility credit spreads, which are more accurate. We use term structure adjusted return of bond index as the systemic risk factor of corporate bond market, the three Fama/French systemic factors as the systemic risk factors of stock markets and idiosyncratic stock/bond volatility and idiosyncratic bond value-at-risk as the idiosyncratic risk factors. Empirical analysis of corporate bonds sampling China’s listing Corporation issued and traded on Shanghai Stock Exchange from 2008 to 2011 shows that the size of credit spreads is mainly determined by the systemic risk factors of bond market, i.e. risk factors of stock market make very little contribution to the spread; the idiosyncratic risk factors also contribute. An interesting phenomenon is that we find that the relationship between idiosyncratic stock volatility and credit spread is negative, which is contrary to extant research while the relationship is positive and mainly focuses on impact of risk factors on credit spread of corporate bond.

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Acknowledgments

This research was supported by the program of the National Natural Science Foundation of China (Grant Nos. 71171176, and 71471161), the key program of the National Natural Science Foundation of China (Grant Nos. 71433001, and 71231005), the Program of Humanities and Social Sciences of Ministry of Education of China (Grant Nos. 11YJC790306, and 12YJC910011), the Fundamental Research Funds for the Central Universities in UIBE (No. 14YQ04).

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Correspondence to Rongda Chen.

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Chen, R., Yang, L., Wang, W. et al. Discovering the impact of systemic and idiosyncratic risk factors on credit spread of corporate bond within the framework of intelligent knowledge management. Ann Oper Res 234, 3–15 (2015). https://doi.org/10.1007/s10479-014-1727-y

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