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Forecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach
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- Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
- Ahmadi, Maryam & Manera, Matteo & Sadeghzadeh, Mehdi, 2019.
"The investment-uncertainty relationship in the oil and gas industry,"
Resources Policy, Elsevier, vol. 63(C), pages 1-1.
- Maryam, Ahmadi & Matteo, Manera & Mehdi, Sadeghzadeh, 2018. "Investment-Uncertainty Relationship in the Oil and Gas Industry," Working Papers 379, University of Milano-Bicocca, Department of Economics, revised 10 Apr 2018.
- Ahmadi, Maryam & Manera, Matteo & Sadeghzadeh, Mehdi, 2018. "Investment-Uncertainty Relationship in the Oil and Gas Industry," ETA: Economic Theory and Applications 273141, Fondazione Eni Enrico Mattei (FEEM).
- Maryam Ahmadi & Matteo Manera & Mehdi Sadeghzadeh, 2018. "Investment-Uncertainty Relationship in the Oil and Gas Industry," Working Papers 2018.13, Fondazione Eni Enrico Mattei.
- Degiannakis, Stavros & Filis, George, 2017.
"Forecasting oil price realized volatility using information channels from other asset classes,"
Journal of International Money and Finance, Elsevier, vol. 76(C), pages 28-49.
- Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," MPRA Paper 96276, University Library of Munich, Germany.
- 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).
- Hedi Ben Haddad & Imed Mezghani & Abdessalem Gouider, 2021. "The Dynamic Spillover Effects of Macroeconomic and Financial Uncertainty on Commodity Markets Uncertainties," Economies, MDPI, vol. 9(2), pages 1-22, June.
- Kenichiro McAlinn, 2021. "Mixed‐frequency Bayesian predictive synthesis for economic nowcasting," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1143-1163, November.
- 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.
- Cheng, Zishu & Li, Mingchen & Sun, Yuying & Hong, Yongmiao & Wang, Shouyang, 2024. "Climate change and crude oil prices: An interval forecast model with interval-valued textual data," Energy Economics, Elsevier, vol. 134(C).
- Kilian, Lutz & Baumeister, Christiane, 2014.
"A General Approach to Recovering Market Expectations from Futures Prices With an Application to Crude Oil,"
CEPR Discussion Papers
10162, C.E.P.R. Discussion Papers.
- Christiane Baumeister & Lutz Kilian, 2016. "A General Approach to Recovering Market Expectations from Futures Prices with an Application to Crude Oil," Staff Working Papers 16-18, Bank of Canada.
- Christiane Baumeister & Lutz Kilian, 2016. "A General Approach to Recovering Market Expectations from Futures Prices with an Application to Crude Oil," CESifo Working Paper Series 5782, CESifo.
- Baumeister, Christiane & Kilian, Lutz, 2014. "A general approach to recovering market expectations from futures prices with an application to crude oil," CFS Working Paper Series 466, Center for Financial Studies (CFS).
- Gupta, Kartick & Banerjee, Rajabrata, 2019. "Does OPEC news sentiment influence stock returns of energy firms in the United States?," Energy Economics, Elsevier, vol. 77(C), pages 34-45.
- Pedro Moreno & Isabel Figuerola-Ferretti & Antonio Muñoz, 2024. "Forecasting Oil Prices with Non-Linear Dynamic Regression Modeling," Energies, MDPI, vol. 17(9), pages 1-29, May.
- Charles W. Calomiris & Nida Çakır Melek & Harry Mamaysky, 2021. "Predicting the Oil Market," NBER Working Papers 29379, National Bureau of Economic Research, Inc.
- Ding Du & Ronald J Gunderson & Xiaobing Zhao, 2016. "Investor sentiment and oil prices," Journal of Asset Management, Palgrave Macmillan, vol. 17(2), pages 73-88, March.
- Van Robays, Ine & Belu Mănescu, Cristiana, 2014.
"Forecasting the Brent oil price: addressing time-variation in forecast performance,"
Working Paper Series
1735, European Central Bank.
- Cristiana Belu Manescu & Ine Van Robays, 2016. "Forecasting the Brent Oil Price: Addressing Time-Variation in Forecast Performance," CESifo Working Paper Series 6242, CESifo.
- Kilian, Lutz & Baumeister, Christiane & Zhou, Xiaoqing, 2013.
"Are Product Spreads Useful for Forecasting? An Empirical Evaluation of the Verleger Hypothesis,"
CEPR Discussion Papers
9572, C.E.P.R. Discussion Papers.
- Baumeister, Christiane & Kilian, Lutz, 2013. "Are product spreads useful for forecasting? An empirical evaluation of the Verleger hypothesis," CFS Working Paper Series 2013/09, Center for Financial Studies (CFS).
- Christiane Baumeister & Lutz Kilian & Xiaoqing Zhou, 2013. "Are Product Spreads Useful for Forecasting? An Empirical Evaluation of the Verleger Hypothesis," Staff Working Papers 13-25, Bank of Canada.
- Arroyo Marioli,Francisco & Khadan,Jeetendra & Ohnsorge,Franziska Lieselotte & Yamazaki,Takefumi, 2023. "Forecasting Industrial Commodity Prices : Literature Review and a Model Suite," Policy Research Working Paper Series 10611, The World Bank.
- Georges Prat & Remzi Uctum, 2024. "Risk premium, price of risk and expected volatility in the oil market: Evidence from survey data," Post-Print hal-04873466, HAL.
- Jha, Nimish & Kumar Tanneru, Hemanth & Palla, Sridhar & Hussain Mafat, Iradat, 2024. "Multivariate analysis and forecasting of the crude oil prices: Part I – Classical machine learning approaches," Energy, Elsevier, vol. 296(C).
- Christiane Baumeister & Dimitris Korobilis & Thomas K. Lee, 2022.
"Energy Markets and Global Economic Conditions,"
The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 828-844, October.
- Christiane Baumeister & Dimitris Korobilis & Thomas K. Lee, 2020. "Energy Markets and Global Economic Conditions," Working Papers 2020_08, Business School - Economics, University of Glasgow.
- Christiane Baumeister & Dimitris Korobilis & Thomas K. Lee, 2020. "Energy Markets and Global Economic Conditions," NBER Working Papers 27001, National Bureau of Economic Research, Inc.
- Baumeister, Christiane & Korobilis, Dimitris & Lee, Thomas K., 2020. "Energy Markets and Global Economic Conditions," CEPR Discussion Papers 14580, C.E.P.R. Discussion Papers.
- Christiane Baumeister & Dimitris Korobilis & Thomas K. Lee, 2020. "Energy Markets and Global Economic Conditions," CESifo Working Paper Series 8282, CESifo.
- Baumeister, Christiane & Kilian, Lutz & Lee, Thomas K., 2014.
"Are there gains from pooling real-time oil price forecasts?,"
Energy Economics, Elsevier, vol. 46(S1), pages 33-43.
- Christiane Baumeister & Lutz Kilian & Thomas K. Lee, 2014. "Are There Gains from Pooling Real-Time Oil Price Forecasts?," Staff Working Papers 14-46, Bank of Canada.
- Kilian, Lutz & Baumeister, Christiane & Lee, Thomas K, 2014. "Are there Gains from Pooling Real-Time Oil Price Forecasts?," CEPR Discussion Papers 10075, C.E.P.R. Discussion Papers.
- Wen, Danyan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2024. "Forecasting crude oil market volatility: A comprehensive look at uncertainty variables," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1022-1041.
- João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
- Rubaszek, Michał, 2021.
"Forecasting crude oil prices with DSGE models,"
International Journal of Forecasting, Elsevier, vol. 37(2), pages 531-546.
- Michał Rubaszek, 2019. "Forecasting crude oil prices with DSGE models," GRU Working Paper Series GRU_2019_024, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
- Verena Monschang & Bernd Wilfling, 2022. "A procedure for upgrading linear-convex combination forecasts with an application to volatility prediction," CQE Working Papers 9722, Center for Quantitative Economics (CQE), University of Muenster.
- Francesco Ravazzolo & Joaquin L. Vespignani, 2015.
"A new monthly indicator of global real economic activity,"
Globalization Institute Working Papers
244, Federal Reserve Bank of Dallas.
- Ravazzolo, Francesco & Vespignani, Joaquin, 2015. "A new monthly indicator of global real economic activity," Working Papers 2015-07, University of Tasmania, Tasmanian School of Business and Economics.
- Francesco Ravazzolo & Joaquin L. Vespignani, 2015. "A New Monthly Indicator of Global Real Economic Activity," CAMA Working Papers 2015-13, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Francesco Ravazzolo & Joaquin L. Vespignani, 2015. "A New Monthly Indicator of Global Real Economic Activity," Working Papers No 2/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Francesco Ravazzolo & Joaquin L. Vespignani, 2015. "A New Monthly Indicator of Global Real Economic Activity," Working Paper 2015/06, Norges Bank.
- Ding, Yishan, 2018. "A novel decompose-ensemble methodology with AIC-ANN approach for crude oil forecasting," Energy, Elsevier, vol. 154(C), pages 328-336.
- John M. Maheu & Yong Song, 2018.
"An efficient Bayesian approach to multiple structural change in multivariate time series,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(2), pages 251-270, March.
- Maheu, John M & Song, Yong, 2017. "An Efficient Bayesian Approach to Multiple Structural Change in Multivariate Time Series," MPRA Paper 79211, University Library of Munich, Germany.
- Qingxiang Han & Mengxi He & Yaojie Zhang & Muhammad Umar, 2023. "Default return spread: A powerful predictor of crude oil price returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1786-1804, November.
- Baumeister, Christiane & Guérin, Pierre & Kilian, Lutz, 2015.
"Do high-frequency financial data help forecast oil prices? The MIDAS touch at work,"
International Journal of Forecasting, Elsevier, vol. 31(2), pages 238-252.
- Kilian, Lutz & Baumeister, Christiane, 2013. "Do High-Frequency Financial Data Help Forecast Oil Prices? The MIDAS Touch at Work," CEPR Discussion Papers 9768, C.E.P.R. Discussion Papers.
- Baumeister, Christiane & Guérin, Pierre & Kilian, Lutz, 2013. "Do high-frequency financial data help forecast oil prices? The MIDAS touch at work," CFS Working Paper Series 2013/22, Center for Financial Studies (CFS).
- Christiane Baumeister & Pierre Guérin & Lutz Kilian, 2014. "Do High-Frequency Financial Data Help Forecast Oil Prices? The MIDAS Touch at Work," Staff Working Papers 14-11, Bank of Canada.
- Wang, Yudong & Liu, Li & Diao, Xundi & Wu, Chongfeng, 2015. "Forecasting the real prices of crude oil under economic and statistical constraints," Energy Economics, Elsevier, vol. 51(C), pages 599-608.
- 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).
- Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Zeng, Zhi-Jian & Gong, Jue, 2024. "Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 673-711.
- Wen, Chufu & Zhu, Haoyang & Dai, Zhifeng, 2023. "Forecasting commodity prices returns: The role of partial least squares approach," Energy Economics, Elsevier, vol. 125(C).
- Christiane Baumeister & Lutz Kilian & Thomas K. Lee, 2017.
"Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 275-295, March.
- Baumeister, Christiane & Kilian, Lutz & Lee, Thomas K., 2015. "Inside the crystal ball: New approaches to predicting the gasoline price at the pump," CFS Working Paper Series 500, Center for Financial Studies (CFS).
- Christiane Baumeister & Lutz Kilian & Thomas K. Lee, 2016. "Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump," CESifo Working Paper Series 5759, CESifo.
- Kilian, Lutz & Baumeister, Christiane & Lee, Thomas K, 2015. "Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump," CEPR Discussion Papers 10362, C.E.P.R. Discussion Papers.
- Ferrari, Davide & Ravazzolo, Francesco & Vespignani, Joaquin, 2021.
"Forecasting energy commodity prices: A large global dataset sparse approach,"
Energy Economics, Elsevier, vol. 98(C).
- Davide Ferrari & Francesco Ravazzolo & Joaquin Vespignani, 2019. "Forecasting Energy Commodity Prices: A Large Global Dataset Sparse Approach," CAMA Working Papers 2019-90, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Davide Ferrari & Francesco Ravazzolo & Joaquin Vespignani, 2021. "Forecasting Energy Commodity Prices: A Large Global Dataset Sparse Approach," BEMPS - Bozen Economics & Management Paper Series BEMPS83, Faculty of Economics and Management at the Free University of Bozen.
- Ferrari, Davide & Ravazzolo, Francesco & Vespignani, Joaquin, 2019. "Forecasting energy commodity prices: a large global dataset sparse approach," Working Papers 2019-09, University of Tasmania, Tasmanian School of Business and Economics.
- Davide Ferrari & Francesco Ravazzolo & Joaquin Vespignani, 2019. "Forecasting Energy Commodity Prices: A Large Global Dataset Sparse Approach," Working Papers No 11/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Davide Ferrari & Francesco Ravazzolo & Joaquin L. Vespignani, 2019. "Forecasting Energy Commodity Prices: A Large Global Dataset Sparse Approach," Globalization Institute Working Papers 376, Federal Reserve Bank of Dallas.
- Zhang, Hui Jun & Dufour, Jean-Marie & Galbraith, John W., 2016.
"Exchange rates and commodity prices: Measuring causality at multiple horizons,"
Journal of Empirical Finance, Elsevier, vol. 36(C), pages 100-120.
- Hui Jun Zhang & Jean-Marie Dufour & John W. Galbraith, 2013. "Exchange rates and commodity prices: measuring causality at multiple horizons," CIRANO Working Papers 2013s-39, CIRANO.
- Hui Jun ZHANG & Jean-Marie DUFOUR & John W. GALBRAITH, 2013. "Exchange Rates and Commodity Prices : Measuring Causality at Multiple Horizons," Cahiers de recherche 14-2013, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- Christian Gourieroux & Joann Jasiak & Michelle Tong, 2021. "Convolution‐based filtering and forecasting: An application to WTI crude oil prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1230-1244, November.
- Pan, Zhiyuan & Pettenuzzo, Davide & Wang, Yudong, 2020.
"Forecasting stock returns: A predictor-constrained approach,"
Journal of Empirical Finance, Elsevier, vol. 55(C), pages 200-217.
- Davide Pettenuzzo & Zhiyuan Pan & Yudong Wang, 2017. "Forecasting Stock Returns: A Predictor-Constrained Approach," Working Papers 116R, Brandeis University, Department of Economics and International Business School, revised Feb 2018.
- Davide Pettenuzzo & Zhiyuan Pan & Yudong Wang, 2017. "Forecasting Stock Returns: A Predictor-Constrained Approach," Working Papers 116, Brandeis University, Department of Economics and International Business School.
- Chu, Pyung Kun & Hoff, Kristian & Molnár, Peter & Olsvik, Magnus, 2022. "Crude oil: Does the futures price predict the spot price?," Research in International Business and Finance, Elsevier, vol. 60(C).
- Maria Lycheva & Alexey Mironenkov & Alexey Kurbatskii & Dean Fantazzini, 2022.
"Forecasting oil prices with penalized regressions, variance risk premia and Google data,"
Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 28-49.
- Fantazzini, Dean & Kurbatskii, Alexey & Mironenkov, Alexey & Lycheva, Maria, 2022. "Forecasting oil prices with penalized regressions, variance risk premia and Google data," MPRA Paper 118239, University Library of Munich, Germany.
- Gonzalo Cortazar & Cristobal Millard & Hector Ortega & Eduardo S. Schwartz, 2019. "Commodity Price Forecasts, Futures Prices, and Pricing Models," Management Science, INFORMS, vol. 65(9), pages 4141-4155, September.
- Xi Wu & Adam Blake, 2023. "Does the combination of models with different explanatory variables improve tourism demand forecasting performance?," Tourism Economics, , vol. 29(8), pages 2032-2056, December.
- Wang, Yudong & Hao, Xianfeng, 2022. "Forecasting the real prices of crude oil: A robust weighted least squares approach," Energy Economics, Elsevier, vol. 116(C).
- Nicholas Apergis, 2023. "Forecasting energy prices: Quantile‐based risk models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 17-33, January.
- Krzysztof Drachal, 2018. "Determining Time-Varying Drivers of Spot Oil Price in a Dynamic Model Averaging Framework," Energies, MDPI, vol. 11(5), pages 1-24, May.
- Jihad El Hokayem & Ibrahim Jamali & Ale Hejase, 2024. "A forecasting model for oil prices using a large set of economic indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1615-1624, August.
- 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.
- Knut Are Aastveit & Jamie L. Cross & Herman K. van Dijk, 2023.
"Quantifying Time-Varying Forecast Uncertainty and Risk for the Real Price of Oil,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(2), pages 523-537, April.
- Knut Are Aastveit & Jamie L. Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Paper 2021/3, Norges Bank.
- Knut Are Aastveit & Jamie Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Tinbergen Institute Discussion Papers 21-053/III, Tinbergen Institute.
- Knut Are Aastveit & Jamie Cross & Herman K. Djik, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Papers No 03/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Francesco Ravazzolo & Joaquin Vespignani, 2020.
"World steel production: A new monthly indicator of global real economic activity,"
Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(2), pages 743-766, May.
- Ravazzolo, Francesco & Vespignani, Joaquin, 2017. "World steel production: A new monthly indicator of global real economic activity," Working Papers 2017-08, University of Tasmania, Tasmanian School of Business and Economics.
- Francesco Ravazzolo & Joaquin Vespignani, 2017. "World steel production: A new monthly indicator of global real economic activity," CAMA Working Papers 2017-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Conny Olovsson, 2019.
"Oil prices in a general equilibrium model with precautionary demand for oil,"
Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 32, pages 1-17, April.
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"Oil prices and fiscal policy in an oil-exporter country: Empirical evidence from Oman,"
Energy Economics, Elsevier, vol. 111(C).
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- Aljabri, Salwa & Raghavan, Mala & Vespignani, Joaquin, 2021. "Oil Prices and Fiscal Policy in an Oil-exporter country: Empirical Evidence from Oman," MPRA Paper 110628, University Library of Munich, Germany.
- Aljabri, Salwa & Raghavan, Mala & Vespignani, Joaquin, 2021. "Oil prices and fiscal policy in an oil-exporter country: empirical evidence from Oman," Working Papers 2021-04, University of Tasmania, Tasmanian School of Business and Economics.
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"Commodity futures return predictability and intertemporal asset pricing,"
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"Forecasting: theory and practice,"
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"Real‐time forecast combinations for the oil price,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 456-462, April.
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"Forecasting oil and stock returns with a Qual VAR using over 150years off data,"
Energy Economics, Elsevier, vol. 62(C), pages 181-186.
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