Decoupling and recoupling in the crude oil price benchmarks: An investigation of similarity patterns
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DOI: 10.1016/j.eneco.2020.105036
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Cited by:
- Ioannis Chatziantoniou & David Gabauer & Rangan Gupta, 2021. "Integration and Risk Transmission in the Market for Crude Oil: A Time-Varying Parameter Frequency Connectedness Approach," Working Papers 202147, University of Pretoria, Department of Economics.
- Loretta Mastroeni & Pierluigi Vellucci, 2022. "Construction of an SDE Model from Intraday Copper Futures Prices," Risks, MDPI, vol. 10(11), pages 1-21, November.
- Chatziantoniou, Ioannis & Gabauer, David & Perez de Gracia, Fernando, 2022. "Tail risk connectedness in the refined petroleum market: A first look at the impact of the COVID-19 pandemic," Energy Economics, Elsevier, vol. 111(C).
- Chatziantoniou, Ioannis & Gabauer, David & Gupta, Rangan, 2023. "Integration and risk transmission in the market for crude oil: New evidence from a time-varying parameter frequency connectedness approach," Resources Policy, Elsevier, vol. 84(C).
- Gao, Xin & Li, Bingxin & Liu, Rui, 2023. "The relative pricing of WTI and Brent crude oil futures: Expectations or risk premia?," Journal of Commodity Markets, Elsevier, vol. 30(C).
- Asit Kumar Das & Debahuti Mishra & Kaberi Das & Pradeep Kumar Mallick & Sachin Kumar & Mikhail Zymbler & Hesham El-Sayed, 2022. "Prophesying the Short-Term Dynamics of the Crude Oil Future Price by Adopting the Survival of the Fittest Principle of Improved Grey Optimization and Extreme Learning Machine," Mathematics, MDPI, vol. 10(7), pages 1-33, March.
- Wang, Tiantian & Qu, Wan & Zhang, Dayong & Ji, Qiang & Wu, Fei, 2022. "Time-varying determinants of China's liquefied natural gas import price: A dynamic model averaging approach," Energy, Elsevier, vol. 259(C).
- Luka Jovanovic & Dejan Jovanovic & Nebojsa Bacanin & Ana Jovancai Stakic & Milos Antonijevic & Hesham Magd & Ravi Thirumalaisamy & Miodrag Zivkovic, 2022. "Multi-Step Crude Oil Price Prediction Based on LSTM Approach Tuned by Salp Swarm Algorithm with Disputation Operator," Sustainability, MDPI, vol. 14(21), pages 1-29, November.
- Mastroeni, Loretta & Mazzoccoli, Alessandro & Vellucci, Pierluigi, 2024. "Studying the impact of fluctuations, spikes and rare events in time series through a wavelet entropy predictability measure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 641(C).
- Liang, Xuedong & Luo, Peng & Li, Xiaoyan & Wang, Xia & Shu, Lingli, 2023. "Crude oil price prediction using deep reinforcement learning," Resources Policy, Elsevier, vol. 81(C).
- Michail Filippidis & George Filis & Georgios Magkonis & Panagiotis Tzouvanas, 2023. "Evaluating robust determinants of the WTI/Brent oil price differential: A dynamic model averaging analysis," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(6), pages 807-825, June.
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- Liang Hu & Yoon‐Jin Lee, 2024. "New evidence on crude oil market efficiency," Economic Inquiry, Western Economic Association International, vol. 62(2), pages 892-916, April.
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Keywords
WTI-Brent decoupling; Market integration; Dynamic time warping;All these keywords.
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