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

Citations

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  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. 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.
  7. 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.
  8. 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).
  9. 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).
  10. Ma, Yong & Li, Shuaibing & Liu, Xiaojun, 2025. "Forecasting energy commodity returns: Can weak factors and nonlinearity help?," Economic Modelling, Elsevier, vol. 153(C).
  11. 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).
  12. 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.
  13. 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.
  14. 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).
  15. 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).
  16. 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).
  17. 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.
  18. Xiaolu Wei & Hongbing Ouyang, 2023. "Forecasting Carbon Price Using Double Shrinkage Methods," IJERPH, MDPI, vol. 20(2), pages 1-20, January.
  19. Zhang, Ditian & Tang, Pan, 2023. "Forecasting European Union allowances futures: The role of technical indicators," Energy, Elsevier, vol. 270(C).
  20. 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.
  21. 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.
  22. 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).
  23. 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.
  24. Jonathan Berrisch & Florian Ziel, 2020. "Distributional Modeling and Forecasting of Natural Gas Prices," Papers 2010.06227, arXiv.org, revised Aug 2021.
  25. 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).
  26. 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.
  27. 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).
  28. 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).
  29. Perry Sadorsky, 2021. "Predicting Gold and Silver Price Direction Using Tree-Based Classifiers," JRFM, MDPI, vol. 14(5), pages 1-21, April.
  30. 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).
  31. 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).
  32. 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.
  33. 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).
  34. Shi, Qi, 2025. "Technical indicators and aggregate stock returns: An updated look," Journal of Multinational Financial Management, Elsevier, vol. 77(C).
  35. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2022. "Geopolitical risk trends and crude oil price predictability," Energy, Elsevier, vol. 258(C).
  36. Plakandaras, Vasilios & Ji, Qiang, 2022. "Intrinsic decompositions in gold forecasting," Journal of Commodity Markets, Elsevier, vol. 28(C).
  37. 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.
  38. Barua, Ronil & Sharma, Anil K., 2022. "Dynamic Black Litterman portfolios with views derived via CNN-BiLSTM predictions," Finance Research Letters, Elsevier, vol. 49(C).
  39. 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).
  40. 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).
  41. 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.
  42. 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).
  43. 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.
  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. 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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