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Credit spread index of fixed income securities in China

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Abstract

Credit risk of fixed income securities is widely concerned during bond trading and risk monitoring, which can be measured by an important economic indicator credit spreads. This paper establishes a credit spread index by GZ model based on yield-to-maturity data of corporate bonds and government bonds from inter-bank bond market in China. In order to analyze the dynamic characteristics of credit spread index, we use GARCH model with Markov-switching process to fit the volatility of credit spread index data and estimate the unknown parameters by MCMC algorithm. The results show that the credit spread index can well reflect the trends and volatilities of the corporate bond credit spreads.

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Acknowledgements

This research was partially supported by NSFC (71471173, 71271210), the Fundamental Research Funds for the Central Universities, the Research Funds of RUC (10XNL007) and the MOE Project of Key Research Institute of Humanities and Social Sciences at Universities (14JJD910002).  The Huishan Wu’s research was partially supported by the Scientific Research Level Improvement Quota Project of Capital University of Economics and Business, the Scientific Research Project of Guangxi Colleges and Universities (KY2015ZD054), the Guangxi Provincial Natural Science Foundation of China (2014GXNSFAA118015).

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Authors and Affiliations

  1. School of Statistics, Capital University of Economics and Business, Beijing, China

    Huishan Wu

  2. College of Science, Guilin University of Technology, Guangxi, China

    Yuanying Jiang

  3. Institute of Food and Nutrition Development, Ministry of Agriculture, Beijing, China

    Yunqian Ma

  4. Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing, China

    Bo Zhang

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  1. Huishan Wu
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  2. Yuanying Jiang
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  3. Yunqian Ma
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  4. Bo Zhang
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Correspondence to Bo Zhang.

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Communicated by Y. Ni.

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Wu, H., Jiang, Y., Ma, Y. et al. Credit spread index of fixed income securities in China. Soft Comput 22, 5625–5630 (2018). https://doi.org/10.1007/s00500-017-2551-5

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  • DOI: https://doi.org/10.1007/s00500-017-2551-5

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