Research on Returns and Volatility Correlations of High-Speed Railway and Related Industries Based on GARCH- Models

Department of Dundee International Institute, Central South University, Changsha, China

^* Corresponding author: 7805220201@csu.edu.cn

Abstract

Volatility and correlation play a significant role in research on the stock market, and they are also be employed to forecast the future trend. This paper conducts a financial test of the volatility of stocks of High-speed rail industry upstream and downstream in China by applying multivariate Generalized Autoregressive Conditional Heteroscedastic Models. Sample data used in this paper are China Securities Index (CSI) 500 Electric Power Equipment Index, CSI High-Speed Railway Industry Index and CSI Tourism Thematic Index. This paper takes daily closing price within the period of 5 years of these three indexes as the object of research. The empirical results show that the distributions of returns exhibit characteristics such as negative skewness, leptokurtosis, and asymmetric distribution. The predicted result of Conditional Mean Equation shows that the returns of one- period lag of CSI High-Speed Railway Industry Index influences CSI 500 Electric Power Equipment Index as well as CSI Tourism Thematic Index have an impact on CSI High-Speed Railway Industry Index significantly. The dynamic conditional correlation coefficient of CSI High-Speed Railway Industry Index and CSI Tourism Thematic Index is positive throughout the entire sample period. Therefore, investor can take these two stocks into consideration together to reduce investment risk.