Research on the Predictive Impact of Global Energy Instability on Chinese Stock Price Volatility of Different Sectors

Authors

  • Rui Liu School of Economics and Management, Nanjing University of Science and Technology, Nanjing, China

DOI:

https://doi.org/10.62051/6tmdqz25

Keywords:

Energy uncertainty; Stock market volatility; Forecast.

Abstract

 In recent years, the global energy supply and demand contradiction has worsened sharply, the international energy price fluctuates frequently, and the global energy instability has become more and more serious under the influence of geopolitical conflicts, climate change, exchange rate fluctuations and other factors. Since energy is an asset with both commodity and financial attributes, rising uncertainty is bound to have an impact on financial markets. Therefore, it is of great significance to explore how global energy instability affects our stock market for the steady development of our financial market and the strategic layout of maintaining financial stability. The subject of this paper is the impact of global energy instability on the prediction of Chinese industrial stock price volatility. In this paper, we choose EUI (energy uncertainty index) which are constructed by Tam Hoang-nhat Dang et al., and 10 Shanghai Stock Exchange Index. Based on autoregressive (AR) model, a volatility forecasting model is established to explore EUI's ability to predict stock volatility both in-sample and out-of-sample. The results show that, firstly, when the prediction horizon is small, the prediction effect of EUI is not significant. And the longer the prediction horizon is, the more significant the prediction effect of EUI on volatility is. Secondly, global energy instability has a negative effect on the volatility of energy, health and utility sectors when the forecast horizon is large. Finally, in out-of-sample predictions one month in advance, EUI has a remarkable ability to predict fluctuations in information technology sector and communication services sector. The conclusion of this paper provides a new way to measure and forecast the fluctuation of stock price from the perspective of the sector.

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Published

13-11-2026