Open Access

ARTICLE

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

Maojun Zhang^1,2, Jiajin Yao¹, Zhonghang Xia³, Jiangxia Nan^1,*, 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.

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Keywords

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

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