Forecasting commodity price indexes using macroeconomic and financial predictors
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Cited by:
- Kuruppuarachchi, Duminda & Premachandra, I.M., 2016. "Information spillover dynamics of the energy futures market sector: A novel common factor approach," Energy Economics, Elsevier, vol. 57(C), pages 277-294.
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"Business cycle, storage, and energy prices,"
Review of Financial Economics, John Wiley & Sons, vol. 23(4), pages 217-226, November.
- Kucher, Oleg & Kurov, Alexander, 2014. "Business cycle, storage, and energy prices," Review of Financial Economics, Elsevier, vol. 23(4), pages 217-226.
- Jesus Crespo Cuaresma & Ines Fortin & Jaroslava Hlouskova & Michael Obersteiner, 2024.
"Regime‐dependent commodity price dynamics: A predictive analysis,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2822-2847, November.
- Crespo-Cuaresma, Jesus & Fortin, Ines & Hlouskova, Jaroslava & Obersteiner, Michael, 2021. "Regime-dependent commodity price dynamics: A predictive analysis," IHS Working Paper Series 28, Institute for Advanced Studies.
- Daskalaki, Charoula & Skiadopoulos, George & Topaloglou, Nikolas, 2017.
"Diversification benefits of commodities: A stochastic dominance efficiency approach,"
Journal of Empirical Finance, Elsevier, vol. 44(C), pages 250-269.
- Charoula Daskalaki & George Skiadopoulos & Nikolas Topaloglou, 2016. "Diversification Benefits of Commodities: A Stochastic Dominance Efficiency Approach," Working Papers 797, Queen Mary University of London, School of Economics and Finance.
- Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2023. "Gold risk premium estimation with machine learning methods," Journal of Commodity Markets, Elsevier, vol. 31(C).
- Rubaszek, Michał & Karolak, Zuzanna & Kwas, Marek, 2020. "Mean-reversion, non-linearities and the dynamics of industrial metal prices. A forecasting perspective," Resources Policy, Elsevier, vol. 65(C).
- Dai, Zhifeng & Kang, Jie & Hu, Yangli, 2021. "Efficient predictability of oil price: The role of number of IPOs and U.S. dollar index," Resources Policy, Elsevier, vol. 74(C).
- Rad, Hossein & Low, Rand Kwong Yew & Miffre, Joëlle & Faff, Robert, 2023.
"The commodity risk premium and neural networks,"
Journal of Empirical Finance, Elsevier, vol. 74(C).
- H. Rad & R. Low & J. Miffre & R. Faff, 2023. "The commodity risk premium and neural networks," Post-Print hal-04322519, HAL.
- Marek Kwas & Michał Rubaszek, 2021. "Forecasting Commodity Prices: Looking for a Benchmark," Forecasting, MDPI, vol. 3(2), pages 1-13, June.
- Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2021. "Economic drivers of commodity volatility: The case of copper," Resources Policy, Elsevier, vol. 73(C).
- Wang, Yudong & Liu, Li & Wu, Chongfeng, 2020. "Forecasting commodity prices out-of-sample: Can technical indicators help?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 666-683.
- Daskalaki, Charoula & Skiadopoulos, George & Topaloglou, Nikolas, 2017.
"Diversification benefits of commodities: A stochastic dominance efficiency approach,"
Journal of Empirical Finance, Elsevier, vol. 44(C), pages 250-269.
- Charoula Daskalaki & George Skiadopoulos & Nikolas Topaloglou, 2016. "Diversification Benefits of Commodities: A Stochastic Dominance Efficiency Approach," Working Papers 797, Queen Mary University of London, School of Economics and Finance.
- Charoula Daskalaki & George Skiadopoulos & Nikolas Topaloglou, 2016. "Diversification Benefits of Commodities: A Stochastic Dominance Efficiency Approach," Working Papers 797, Queen Mary University of London, School of Economics and Finance.
- Hollstein, Fabian & Prokopczuk, Marcel & Tharann, Björn & Wese Simen, Chardin, 2021. "Predictability in commodity markets: Evidence from more than a century," Journal of Commodity Markets, Elsevier, vol. 24(C).
- Rehman, Mobeen Ur & Zeitun, Rami & Mardani, Abbas & Vo, Xuan Vinh & Eraslan, Veysel, 2022. "Asymmetric pass through of energy commodities to US sectoral returns," Resources Policy, Elsevier, vol. 76(C).
- Tapia Cortez, Carlos A. & Hitch, Michael & Sammut, Claude & Coulton, Jeff & Shishko, Robert & Saydam, Serkan, 2018. "Determining the embedding parameters governing long-term dynamics of copper prices," Chaos, Solitons & Fractals, Elsevier, vol. 111(C), pages 186-197.
- Ye, Wuyi & Guo, Ranran & Deschamps, Bruno & Jiang, Ying & Liu, Xiaoquan, 2021. "Macroeconomic forecasts and commodity futures volatility," Economic Modelling, Elsevier, vol. 94(C), pages 981-994.
- Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021.
"Machine learning and oil price point and density forecasting,"
Energy Economics, Elsevier, vol. 102(C).
- Alexandre Bonnet R. Costa & Pedro Cavalcanti G. Ferreira & Wagner P. Gaglianone & Osmani Teixeira C. Guillén & João Victor Issler & Yihao Lin, 2021. "Machine Learning and Oil Price Point and Density Forecasting," Working Papers Series 544, Central Bank of Brazil, Research Department.
- Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2017. "Predictability and diversification benefits of investing in commodity and currency futures," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 52-66.
- Cheng, Xian & Wu, Peng & Liao, Stephen Shaoyi & Wang, Xuelian, 2023. "An integrated model for crude oil forecasting: Causality assessment and technical efficiency," Energy Economics, Elsevier, vol. 117(C).
- Libo Yin & Liyan Han, 2016. "Macroeconomic impacts on commodity prices: China vs. the United States," Quantitative Finance, Taylor & Francis Journals, vol. 16(3), pages 489-500, March.
- Rubaszek Michal & Karolak Zuzanna & Kwas Marek & Uddin Gazi Salah, 2020. "The role of the threshold effect for the dynamics of futures and spot prices of energy commodities," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(5), pages 1-20, December.
- Pablo Pincheira-Brown & Nicolás Hardy & Cristobal Henrriquez & Ignacio Tapia & Andrea Bentancor, 2023.
"Forecasting Base Metal Prices with an International Stock Index,"
Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 73(3), pages 277-302, October.
- Pincheira, Pablo & Hardy, Nicolas & Bentancor, Andrea & Henriquez, Cristóbal & Tapia, Ignacio, 2021. "Forecasting Base Metal Prices with an International Stock Index," MPRA Paper 107828, University Library of Munich, Germany.
- Ye, Wuyi & Guo, Ranran & Jiang, Ying & Liu, Xiaoquan & Deschamps, Bruno, 2019. "Professional macroeconomic forecasts and Chinese commodity futures prices," Finance Research Letters, Elsevier, vol. 28(C), pages 130-136.
- Angelidis, Timotheos & Sakkas, Athanasios & Tessaromatis, Nikolaos, 2025. "Predicting commodity returns: Time series vs. cross sectional prediction models," Journal of Commodity Markets, Elsevier, vol. 38(C).
- Massimo Guidolin & Manuela Pedio, 2021. "Forecasting commodity futures returns with stepwise regressions: Do commodity-specific factors help?," Annals of Operations Research, Springer, vol. 299(1), pages 1317-1356, April.
- Pincheira, Pablo & Hardy, Nicolás, 2021.
"Forecasting aluminum prices with commodity currencies,"
Resources Policy, Elsevier, vol. 73(C).
- Pincheira, Pablo & Hardy, Nicolás, 2019. "Forecasting Aluminum Prices with Commodity Currencies," MPRA Paper 97005, University Library of Munich, Germany.
- Nonejad, Nima, 2020. "An observation regarding Hamilton’s recent criticisms of Kilian’s global real economic activity index," Economics Letters, Elsevier, vol. 196(C).
- Salisu, Afees A. & Adediran, Idris A. & Oloko, Tirimisiyu O. & Ohemeng, William, 2020. "The heterogeneous behaviour of the inflation hedging property of cocoa," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
- Hammami, Yacine & Zhu, Jie, 2020. "Understanding time-varying short-horizon predictability✰," Finance Research Letters, Elsevier, vol. 32(C).
- Chen, Xiangyu & Tongurai, Jittima, 2021. "Cross-commodity hedging for illiquid futures: Evidence from China's base metal futures market," Global Finance Journal, Elsevier, vol. 49(C).
- Qin Yiyi & Jun Cai & Jie Zhu & Robert Webb, 2025. "Commodity Futures Characteristics and Asset Pricing Models," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(3), pages 176-207, March.
- Fernandez, Viviana, 2020. "The predictive power of convenience yields," Resources Policy, Elsevier, vol. 65(C).
- 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).
- Zhou, Mingtao & Ma, Yong, 2025. "Climate risk and predictability of global stock market volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 101(C).
- James D. Hamilton, 2019. "Measuring Global Economic Activity," NBER Working Papers 25778, National Bureau of Economic Research, Inc.
- Ma, Feng & Liu, Jing & Wahab, M.I.M. & Zhang, Yaojie, 2018. "Forecasting the aggregate oil price volatility in a data-rich environment," Economic Modelling, Elsevier, vol. 72(C), pages 320-332.
- Bohl, Martin T. & Pütz, Alexander & Sulewski, Christoph, 2021. "Speculation and the informational efficiency of commodity futures markets," Journal of Commodity Markets, Elsevier, vol. 23(C).
- Massimo Guidolin & Manuela Pedio, 2018. "Forecasting Commodity Futures Returns: An Economic Value Analysis of Macroeconomic vs. Specific Factors," BAFFI CAREFIN Working Papers 1886, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
- Krzysztof Drachal, 2018. "Some Novel Bayesian Model Combination Schemes: An Application to Commodities Prices," Sustainability, MDPI, vol. 10(8), pages 1-27, August.
- Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2023.
"Commodity futures return predictability and intertemporal asset pricing,"
Journal of Commodity Markets, Elsevier, vol. 31(C).
- John Cotter & Emmanuel Eyiah-Donkor & Valerio Potì, 2020. "Commodity Futures Return Predictability and Intertemporal Asset Pricing," Working Papers 202011, Geary Institute, University College Dublin.
- John Cotter & Emmanuel Eyiah-Donkor & Valerio Potì, 2023. "Commodity futures return predictability and intertemporal asset pricing," Post-Print hal-04192933, HAL.
- Güllü, Refik & Erkip, Nesim, 2024. "Risk pooling under demand and price uncertainty," European Journal of Operational Research, Elsevier, vol. 315(1), pages 120-129.
- Drachal, Krzysztof, 2018. "Comparison between Bayesian and information-theoretic model averaging: Fossil fuels prices example," Energy Economics, Elsevier, vol. 74(C), pages 208-251.
- Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2022. "Forecasting European carbon returns using dimension reduction techniques: Commodity versus financial fundamentals," International Journal of Forecasting, Elsevier, vol. 38(3), pages 944-969.
- 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).
- Pincheira, Pablo & Hardy, Nicolas, 2018. "Forecasting Base Metal Prices with Commodity Currencies," MPRA Paper 83564, University Library of Munich, Germany.
- Allayioti, Anastasia & Venditti, Fabrizio, 2024. "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series 2901, European Central Bank.
- Pincheira, Pablo & Hardy, Nicolas, 2018. "The predictive relationship between exchange rate expectations and base metal prices," MPRA Paper 89423, University Library of Munich, Germany.
- Abhibasu Sen & Karabi Dutta Choudhury & Tapan Kumar Datta, 2023. "An analysis of crude oil prices in the last decade (2011-2020): With deep learning approach," PLOS ONE, Public Library of Science, vol. 18(3), pages 1-32, March.
- Iason Kynigakis & Ekaterini Panopoulou, 2022. "Does model complexity add value to asset allocation? Evidence from machine learning forecasting models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 603-639, April.
- Farid, Saqib & Naeem, Muhammad Abubakr & Paltrinieri, Andrea & Nepal, Rabindra, 2022. "Impact of COVID-19 on the quantile connectedness between energy, metals and agriculture commodities," Energy Economics, Elsevier, vol. 109(C).
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- Liu, Chang & Hu, Zhenhua & Li, Yan & Liu, Shaojun, 2017. "Forecasting copper prices by decision tree learning," Resources Policy, Elsevier, vol. 52(C), pages 427-434.
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- Charalampos Stasinakis & Georgios Sermpinis & Ioannis Psaradellis & Thanos Verousis, 2016. "Krill-Herd Support Vector Regression and heterogeneous autoregressive leverage: evidence from forecasting and trading commodities," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1901-1915, December.
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"Forecasting copper prices with dynamic averaging and selection models,"
The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 1-38.
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"The macroeconomic response to real and financial factors, commodity prices, and monetary policy: International evidence,"
Economic Systems, Elsevier, vol. 45(1).
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- Jesus Crespo Cuaresma & Jaroslava Hlouskova & Michael Obersteiner, 2021. "Agricultural commodity price dynamics and their determinants: A comprehensive econometric approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1245-1273, November.
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- Jia, Jian & Kang, Sang Baum, 2022. "Do the basis and other predictors of futures return also predict spot return with the same signs and magnitudes? Evidence from the LME," Journal of Commodity Markets, Elsevier, vol. 25(C).
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"On the influence of US monetary policy on crude oil price volatility,"
Empirical Economics, Springer, vol. 52(1), pages 155-178, February.
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