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China’s Energy Stock Price Index Prediction Based on VECM–BiLSTM Model

Author

Listed:
  • Bingchun Liu

    (School of Management, Tianjin University of Technology, Tianjin 300382, China)

  • Xia Zhang

    (School of Management, Tianjin University of Technology, Tianjin 300382, China)

  • Yuan Gao

    (Xinhua Electric Power Development Investment Co., Ltd., CNNC, Tianjin 300382, China)

  • Minghui Xu

    (China Energy Engineering Group Tianjin Electric Power Design Institute Co., Ltd., Tianjin 300382, China)

  • Xiaobo Wang

    (Office of State-Owned Assets and Campus Economic Management, Tianjin University of Technology, Tianjin 300382, China)

Abstract

The energy stock price index maps the development trends in China’s energy market to a certain extent, and accurate forecasting of China’s energy market index can effectively guide the government to regulate energy policies to cope with external risks. The vector error correction model (VECM) analyzes the relationship between each indicator and the output, provides an external explanation for the way the indicator influences the output indicator, and uses this to filter the input indicators. The forecast results of the China energy stock price index for 2022–2024 showed an upward trend, and the model evaluation parameters MAE, MAPE, and RMSE were 0.2422, 3.5704% and 0.3529, respectively, with higher forecasting efficiency than other comparative models. Finally, the impact of different indicators on the Chinese energy market was analyzed through scenario setting. The results show that oscillations in the real commodity price factor (RCPF) and the global economic conditions index (GECON) cause fluctuations in the price indices of the Chinese energy market and that the Chinese energy market evolves in the same manner as the changes in two international stock indices: the MSCI World Index and FTSE 100 Index.

Suggested Citation

  • Bingchun Liu & Xia Zhang & Yuan Gao & Minghui Xu & Xiaobo Wang, 2025. "China’s Energy Stock Price Index Prediction Based on VECM–BiLSTM Model," Energies, MDPI, vol. 18(5), pages 1-21, March.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:5:p:1242-:d:1604619
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