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Forecasting crude oil prices: A reduced-rank approach

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  • Song, Yixuan
  • He, Mengxi
  • Wang, Yudong
  • Zhang, Yaojie

Abstract

We use a reduced-rank approach (RRA) to forecast oil prices. The empirical results show that the RRA model outperforms the competitive models both in-sample and out-of-sample. We also find that the RRA model can generate economic value for investors. In addition, we explore the driving force of RRA's predictive power and show that the RRA model can effectively identify the predictive information of indicators, including magnitude and direction, and apply appropriate loadings to the predictors accordingly. Finally, our results are robust to multiple alternatives.

Suggested Citation

  • Song, Yixuan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2023. "Forecasting crude oil prices: A reduced-rank approach," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 698-711.
    • Handle: RePEc:eee:reveco:v:88:y:2023:i:c:p:698-711
    DOI: 10.1016/j.iref.2023.07.001
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    Cited by:

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    8. Ouyang, Zisheng & Lu, Min & Ouyang, Zhongzhe & Zhou, Xuewei & Wang, Ren, 2024. "A novel integrated method for improving the forecasting accuracy of crude oil: ESMD-CFastICA-BiLSTM-Attention," Energy Economics, Elsevier, vol. 138(C).
    9. Xiaotao Zhang & Zihui Xia & Feng He & Jing Hao, 2025. "Forecasting crude oil prices with alternative data and a deep learning approach," Annals of Operations Research, Springer, vol. 345(2), pages 1165-1191, February.
    10. Gong, Xue & Ji, Shidong & Zhang, Yaojie, 2025. "Attention to climate events and carbon price volatility," Finance Research Letters, Elsevier, vol. 79(C).
    11. Dehao Dai & Ding Ma & Dou Liu & Kerui Geng & Yiqing Wang, 2026. "Beyond Polarity: Multi-Dimensional LLM Sentiment Signals for WTI Crude Oil Futures Return Prediction," Papers 2603.11408, arXiv.org, revised Mar 2026.
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    Keywords

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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