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Forecasting commodity prices out-of-sample: Can technical indicators help?

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Cited by:

  1. Pan, Zhiyuan & Zhong, Hao & Wang, Yudong & Huang, Juan, 2024. "Forecasting oil futures returns with news," Energy Economics, Elsevier, vol. 134(C).
  2. Kyungbo Park & Hangook Kim & Jeonghwa Cha, 2023. "An Exploratory Study on the Development of a Crisis Index: Focusing on South Korea’s Petroleum Industry," Energies, MDPI, vol. 16(14), pages 1-24, July.
  3. Henriques, Irene & Sadorsky, Perry, 2023. "Forecasting rare earth stock prices with machine learning," Resources Policy, Elsevier, vol. 86(PA).
  4. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
  5. Wen, Chufu & Zhu, Haoyang & Dai, Zhifeng, 2023. "Forecasting commodity prices returns: The role of partial least squares approach," Energy Economics, Elsevier, vol. 125(C).
  6. Wen, Danyan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2025. "Forecasting gasoline prices using oil prices: New evidence based on the rocket and feather hypothesis," Energy, Elsevier, vol. 335(C).
  7. Zhang, Yaojie & Wang, Yudong, 2023. "Forecasting crude oil futures market returns: A principal component analysis combination approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 659-673.
  8. Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
  9. Zhufeng Wang & Lu Wang & Zitao Zhang, 2026. "Predicting New Energy Prices: Are Technical Indicators and Regime-Switching Models Helpful?," Evaluation Review, , vol. 50(3), pages 315-345, June.
  10. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
  11. Vecchi, Edoardo & Berra, Gabriele & Albrecht, Steffen & Gagliardini, Patrick & Horenko, Illia, 2023. "Entropic approximate learning for financial decision-making in the small data regime," Research in International Business and Finance, Elsevier, vol. 65(C).
  12. Wang, Binjie & Dai, Xingyu & Wang, Qunwei & Wang, Yifei, 2026. "What factors play an important role in crude oil returns forecasting? New evidence from group predictors and multiple time scales," Journal of Commodity Markets, Elsevier, vol. 42(C).
  13. Perry Sadorsky, 2021. "Predicting Gold and Silver Price Direction Using Tree-Based Classifiers," JRFM, MDPI, vol. 14(5), pages 1-21, April.
  14. Ma, Yong & Li, Shuaibing & Liu, Xiaojun, 2025. "Forecasting energy commodity returns: Can weak factors and nonlinearity help?," Economic Modelling, Elsevier, vol. 153(C).
  15. Choi, Insu & Kim, Woo Chang, 2024. "Practical forecasting of risk boundaries for industrial metals and critical minerals via statistical machine learning techniques," International Review of Financial Analysis, Elsevier, vol. 94(C).
  16. Zhao, Yuan & Gong, Xue & Zhang, Weiguo & Xu, Weijun, 2024. "Forecasting carbon futures returns using feature selection and Markov chain with sample distribution," Energy Economics, Elsevier, vol. 140(C).
  17. Yufeng Lin & Xiaogang Wang & Yuehua Wu, 2023. "An Adaptive Multiple-Asset Portfolio Strategy with User-Specified Risk Tolerance," Mathematics, MDPI, vol. 11(7), pages 1-35, March.
  18. Sadorsky, Perry, 2022. "Forecasting solar stock prices using tree-based machine learning classification: How important are silver prices?," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
  19. Papenfuß, Patric & Schischke, Amelie & Rathgeber, Andreas, 2025. "Factors of predictive power for metal commodities," The North American Journal of Economics and Finance, Elsevier, vol. 76(C).
  20. Shi, Qi, 2025. "Technical indicators and aggregate stock returns: An updated look," Journal of Multinational Financial Management, Elsevier, vol. 77(C).
  21. Ajim Uddin & Ummahani Akter & M. Kabir Hassan, 2026. "Significance of Technical Indicators in the Era of Machine Learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 45(4), pages 1559-1578, July.
  22. 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.
  23. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2022. "Geopolitical risk trends and crude oil price predictability," Energy, Elsevier, vol. 258(C).
  24. Plakandaras, Vasilios & Ji, Qiang, 2022. "Intrinsic decompositions in gold forecasting," Journal of Commodity Markets, Elsevier, vol. 28(C).
  25. Zhang, Yue-Jun & Li, Zhao-Chen, 2021. "Forecasting the stock returns of Chinese oil companies: Can investor attention help?," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 531-555.
  26. Jiqian Wang & Feng Ma & Elie Bouri & Yangli Guo, 2023. "Which factors drive Bitcoin volatility: Macroeconomic, technical, or both?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 970-988, July.
  27. Ma, Yong & Zhou, Mingtao & Li, Shuaibing, 2024. "Weathering market swings: Does climate risk matter for agricultural commodity price predictability?," Journal of Commodity Markets, Elsevier, vol. 36(C).
  28. Barua, Ronil & Sharma, Anil K., 2022. "Dynamic Black Litterman portfolios with views derived via CNN-BiLSTM predictions," Finance Research Letters, Elsevier, vol. 49(C).
  29. Khan, Faridoon & Muhammadullah, Sara & Sharif, Arshian & Lee, Chien-Chiang, 2024. "The role of green energy stock market in forecasting China's crude oil market: An application of IIS approach and sparse regression models," Energy Economics, Elsevier, vol. 130(C).
  30. Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Long, Jian-You & Zhou, Yang, 2023. "Forecasting stock market volatility under parameter and model uncertainty," Research in International Business and Finance, Elsevier, vol. 66(C).
  31. Hardy, Nicolás & Ferreira, Tiago & Quinteros, Maria J. & Magner, Nicolás S., 2023. "“Watch your tone!”: Forecasting mining industry commodity prices with financial report tone," Resources Policy, Elsevier, vol. 86(PA).
  32. Yilin Ma & Yudong Wang & Weizhong Wang, 2026. "Forecasting crude oil prices: a novel model combined multisource predictors, factor screening, and forecast combination," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 12(1), pages 1-37, December.
  33. Xiaolu Wei & Hongbing Ouyang, 2023. "Forecasting Carbon Price Using Double Shrinkage Methods," IJERPH, MDPI, vol. 20(2), pages 1-20, January.
  34. Pagnini, Luisa & Bracco, Stefano & Delfino, Federico & de-Simón-Martín, Miguel, 2024. "Levelized cost of electricity in renewable energy communities: Uncertainty propagation analysis," Applied Energy, Elsevier, vol. 366(C).
  35. Zhang, Ditian & Tang, Pan, 2023. "Forecasting European Union allowances futures: The role of technical indicators," Energy, Elsevier, vol. 270(C).
  36. Vasilios Plakandaras & Ioannis Pragidis & Paris Karypidis, 2024. "Deciphering the U.S. metropolitan house price dynamics," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 52(2), pages 434-485, March.
  37. Syed Abul, Basher & Perry, Sadorsky, 2022. "Forecasting Bitcoin price direction with random forests: How important are interest rates, inflation, and market volatility?," MPRA Paper 113293, University Library of Munich, Germany.
  38. Jonathan Berrisch & Florian Ziel, 2022. "Distributional modeling and forecasting of natural gas prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1065-1086, September.
  39. Li, Kaixin & Zhang, Zhikai & Wang, Yudong & Zhang, Yaojie, 2024. "Forecasting crude oil returns with oil-related industry ESG indices," Journal of Commodity Markets, Elsevier, vol. 36(C).
  40. Zhang, Zhikai & Wang, Yudong & Zhang, Yaojie & Wang, Qunwei, 2024. "Forecasting carbon prices under diversified attention: A dynamic model averaging approach with common factors," Energy Economics, Elsevier, vol. 133(C).
  41. Quanbiao Shang & Teresa Serra & Philip Garcia, 2023. "Ride the trend: Is there spread momentum profit in the US commodity markets?," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(1), pages 24-47, February.
  42. Wen, Danyan & Wang, Yudong & Zhang, Yaojie, 2021. "Intraday return predictability in China’s crude oil futures market: New evidence from a unique trading mechanism," Economic Modelling, Elsevier, vol. 96(C), pages 209-219.
  43. Jonathan Berrisch & Florian Ziel, 2020. "Distributional Modeling and Forecasting of Natural Gas Prices," Papers 2010.06227, arXiv.org, revised Aug 2021.
  44. Xiafei Li & Chao Liang & Feng Ma, 2025. "Forecasting stock market volatility with a large number of predictors: New evidence from the MS-MIDAS-LASSO model," Annals of Operations Research, Springer, vol. 352(3), pages 613-652, September.
  45. Gong, Xue & Ye, Xin & Zhang, Weiguo & Zhang, Yue, 2023. "Predicting energy futures high-frequency volatility using technical indicators: The role of interaction," Energy Economics, Elsevier, vol. 119(C).
  46. Xiaolu Wei & Hongbing Ouyang, 2024. "Carbon price prediction based on a scaled PCA approach," PLOS ONE, Public Library of Science, vol. 19(1), pages 1-16, January.
  47. Perry Sadorsky, 2021. "A Random Forests Approach to Predicting Clean Energy Stock Prices," JRFM, MDPI, vol. 14(2), pages 1-20, January.
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