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The Volatility of High-Yield Bonds Using Mixed Data Sampling Methods

Maojun Zhang1,2, Jiajin Yao1, Zhonghang Xia3, Jiangxia Nan1,*, Cuiqing Zhang1
1 Department of Computational Science and Mathematics, Guilin University of Electronic Technology, Guilin, 541004, China.
2 Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation, Guilin University of Electronic Technology, Guilin, 541004, China.
3 School of Engineering and Applied Science, Western Kentucky University, KY, 42101, America.
* Corresponding Author: Jiangxia Nan. Email: zhang1977108@sina.com.

Computers, Materials & Continua 2019, 61(3), 1233-1244. https://doi.org/10.32604/cmc.2019.06118

Abstract

It is well known that economic policy uncertainty prompts the volatility of the high-yield bond market. However, the correlation between economic policy uncertainty and volatility of high-yield bonds is still not clear. In this paper, we employ GARCH-MIDAS models to investigate their correlation with US economic policy uncertainty index and S&P high-yield bond index. The empirical studies show that mixed volatility models can effectively capture the realized volatility of high-yield bonds, and economic policy uncertainty and macroeconomic factors have significant effects on the long-term component of high-yield bonds volatility.

Keywords

High-yield bonds, economic policy, garch-midas, macroeconomic.

Cite This Article

M. Zhang, J. Yao, Z. Xia, J. Nan and C. Zhang, "The volatility of high-yield bonds using mixed data sampling methods," Computers, Materials & Continua, vol. 61, no.3, pp. 1233–1244, 2019.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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