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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 2018.13, Fondazione Eni Enrico Mattei.
- 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 379, University of Milano-Bicocca, Department of Economics, revised 10 Apr 2018.
- 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.
- 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).
- 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.
- 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," 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).
- 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.
- 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.
- 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.
- 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).
- 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.
- 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 Paper 2015/06, Norges Bank.
- 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.
- 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.
- 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.
- 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.
- 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).
- Lycheva, Maria & Mironenkov, Alexey & Kurbatskii, Alexey & Fantazzini, Dean, 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,"
Journal of Commodity Markets, Elsevier, vol. 31(C).
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"The illusion of oil return predictability: The choice of data matters!,"
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"Forecasting: theory and practice,"
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- Anthony Garratt & Shaun P. Vahey & Yunyi Zhang, 2019.
"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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- Pincheira, Pablo & Jarsun, Nabil, 2020. "Summary of the Paper Entitled: Forecasting Fuel Prices with the Chilean Exchange Rate," MPRA Paper 105056, University Library of Munich, Germany.
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