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Soft Computing

, Volume 22, Issue 17, pp 5625–5630 | Cite as

Credit spread index of fixed income securities in China

  • Huishan Wu
  • Yuanying Jiang
  • Yunqian Ma
  • Bo Zhang
Focus

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.

Keywords

Fixed income securities Credit spread index Credit risk Markov-switching 

Notes

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).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.School of StatisticsCapital University of Economics and BusinessBeijingChina
  2. 2.College of ScienceGuilin University of TechnologyGuangxiChina
  3. 3.Institute of Food and Nutrition DevelopmentMinistry of AgricultureBeijingChina
  4. 4.Center for Applied Statistics, School of StatisticsRenmin University of ChinaBeijingChina

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