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A new approach for crude oil price analysis based on Empirical Mode Decomposition

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  1. Liu, Chang & Sun, Xiaolei & Wang, Jun & Li, Jianping & Chen, Jianming, 2021. "Multiscale information transmission between commodity markets: An EMD-Based transfer entropy network," Research in International Business and Finance, Elsevier, vol. 55(C).
  2. Xia, Tongshui & Ji, Qiang & Geng, Jiang-Bo, 2020. "Nonlinear dependence and information spillover between electricity and fuel source markets: New evidence from a multi-scale analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
  3. Wen, Jun & Zhao, Xin-Xin & Chang, Chun-Ping, 2021. "The impact of extreme events on energy price risk," Energy Economics, Elsevier, vol. 99(C).
  4. Ding, Yishan, 2018. "A novel decompose-ensemble methodology with AIC-ANN approach for crude oil forecasting," Energy, Elsevier, vol. 154(C), pages 328-336.
  5. Liu, Hui & Chen, Chao & Tian, Hong-qi & Li, Yan-fei, 2012. "A hybrid model for wind speed prediction using empirical mode decomposition and artificial neural networks," Renewable Energy, Elsevier, vol. 48(C), pages 545-556.
  6. Wang, Delu & Wang, Yadong & Song, Xuefeng & Liu, Yun, 2018. "Coal overcapacity in China: Multiscale analysis and prediction," Energy Economics, Elsevier, vol. 70(C), pages 244-257.
  7. Zhen-Hua Feng & Chun-Feng Liu & Yi-Ming Wei, 2011. "How does carbon price change? Evidences from EU ETS," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 35(2/3/4), pages 132-144.
  8. Lai, Lin & Guo, Kun, 2017. "The performance of one belt and one road exchange rate: Based on improved singular spectrum analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 299-308.
  9. Li, Mingchen & Cheng, Zishu & Lin, Wencan & Wei, Yunjie & Wang, Shouyang, 2023. "What can be learned from the historical trend of crude oil prices? An ensemble approach for crude oil price forecasting," Energy Economics, Elsevier, vol. 123(C).
  10. Geng, Jiang-Bo & Ji, Qiang & Fan, Ying, 2016. "The behaviour mechanism analysis of regional natural gas prices: A multi-scale perspective," Energy, Elsevier, vol. 101(C), pages 266-277.
  11. Bangzhu Zhu & Shujiao Ma & Rui Xie & Julien Chevallier & Yi-Ming Wei, 2018. "Hilbert Spectra and Empirical Mode Decomposition: A Multiscale Event Analysis Method to Detect the Impact of Economic Crises on the European Carbon Market," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 105-121, June.
  12. Ming, Lei & Yang, Shenggang & Cheng, Cheng, 2016. "The double nature of the price of gold—A quantitative analysis based on Ensemble Empirical Mode Decomposition," Resources Policy, Elsevier, vol. 47(C), pages 125-131.
  13. Tao XIONG & Chongguang LI & Yukun BAO, 2017. "An improved EEMD-based hybrid approach for the short-term forecasting of hog price in China," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 63(3), pages 136-148.
  14. Wang, Fan & Tian, Lixin & Du, Ruijin & Dong, Gaogao, 2021. "Universal law in the crude oil market based on visibility graph algorithm and network structure," Resources Policy, Elsevier, vol. 70(C).
  15. Kaijian He & Rui Zha & Jun Wu & Kin Keung Lai, 2016. "Multivariate EMD-Based Modeling and Forecasting of Crude Oil Price," Sustainability, MDPI, vol. 8(4), pages 1-11, April.
  16. Ya-Wen Lai, 2017. "Output gaps and the New Keynesian Phillips curve: An application of the Empirical Mode Decomposition," Economics Bulletin, AccessEcon, vol. 37(2), pages 952-961.
  17. Umar Tijjani Babuga & Niaz Ahmad Mohd Naseem, 2022. "Oil Price Change and Economic Growth: Evidence from Net Sub-Saharan Africa Oil Exporting Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 12(2), pages 369-378, March.
  18. Wang, Haoyu & Di, Junpeng & Yang, Zhaojun & Han, Qing, 2020. "Assessment of mutual fund performance based on Ensemble Empirical Mode Decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
  19. Jihong Xiao & Xuehong Zhu & Chuangxia Huang & Xiaoguang Yang & Fenghua Wen & Meirui Zhong, 2019. "A New Approach for Stock Price Analysis and Prediction Based on SSA and SVM," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 287-310, January.
  20. Chen Weiguo & Zhou Shufen & Zhang Yin & Sun Yi, 2021. "A Study of Multi-Scale Relationship Between Investor Sentiment and Stock Index Fluctuation Based on the Analysis of BEMD Spillover Index," Journal of Systems Science and Information, De Gruyter, vol. 9(4), pages 399-420, August.
  21. Long, Wen & Zhao, Manyi & Tang, Yeran, 2021. "Can the Chinese volatility index reflect investor sentiment?," International Review of Financial Analysis, Elsevier, vol. 73(C).
  22. Taiyong Li & Min Zhou & Chaoqi Guo & Min Luo & Jiang Wu & Fan Pan & Quanyi Tao & Ting He, 2016. "Forecasting Crude Oil Price Using EEMD and RVM with Adaptive PSO-Based Kernels," Energies, MDPI, vol. 9(12), pages 1-21, December.
  23. Jin Chen & Yue Chen & Wei Zhou, 2024. "Relation exploration between clean and fossil energy markets when experiencing climate change uncertainties: substitutes or complements?," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-17, December.
  24. Sun, Shaolong & Sun, Yuying & Wang, Shouyang & Wei, Yunjie, 2018. "Interval decomposition ensemble approach for crude oil price forecasting," Energy Economics, Elsevier, vol. 76(C), pages 274-287.
  25. Yu, Lean & Wang, Zishu & Tang, Ling, 2015. "A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting," Applied Energy, Elsevier, vol. 156(C), pages 251-267.
  26. Li, Songsong & Zhang, Weiqian & Zhang, Wei, 2023. "Dynamic time-frequency connectedness and risk spillover between geopolitical risks and natural resources," Resources Policy, Elsevier, vol. 82(C).
  27. Jaweriah HAZRANA & Aaisha NAZRANA, 2017. "An enquiry into the dynamics of real oil prices: A state space approach," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(2(611), S), pages 197-212, Summer.
  28. Babak Fazelabdolabadi, 2019. "A hybrid Bayesian-network proposition for forecasting the crude oil price," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-21, December.
  29. Tang, Ling & Yu, Lean & He, Kaijian, 2014. "A novel data-characteristic-driven modeling methodology for nuclear energy consumption forecasting," Applied Energy, Elsevier, vol. 128(C), pages 1-14.
  30. Nataša Glišović & Miloš Milenković & Nebojša Bojović & Libor Švadlenka & Zoran Avramović, 2016. "A hybrid model for forecasting the volume of passenger flows on Serbian railways," Operational Research, Springer, vol. 16(2), pages 271-285, July.
  31. Sun, Xiaolei & Tang, Ling & Yang, Yuying & Wu, Dengsheng & Li, Jianping, 2014. "Identifying the dynamic relationship between tanker freight rates and oil prices: In the perspective of multiscale relevance," Economic Modelling, Elsevier, vol. 42(C), pages 287-295.
  32. Inacio, C.M.C. & Kristoufek, L. & David, S.A., 2023. "Assessing the impact of the Russia–Ukraine war on energy prices: A dynamic cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
  33. Wang, Yamin & Wu, Lei, 2016. "On practical challenges of decomposition-based hybrid forecasting algorithms for wind speed and solar irradiation," Energy, Elsevier, vol. 112(C), pages 208-220.
  34. He, Kaijian & Lai, Kin Keung & Yen, Jerome, 2011. "Value-at-risk estimation of crude oil price using MCA based transient risk modeling approach," Energy Economics, Elsevier, vol. 33(5), pages 903-911, September.
  35. Myeong Jun Kim & Stanley I. M. Ko & Sung Y. Park, 2021. "On time and frequency-varying Okun’s coefficient: a new approach based on ensemble empirical mode decomposition," Empirical Economics, Springer, vol. 61(3), pages 1151-1188, September.
  36. Wen-chuan Wang & Kwok-wing Chau & Dong-mei Xu & Xiao-Yun Chen, 2015. "Improving Forecasting Accuracy of Annual Runoff Time Series Using ARIMA Based on EEMD Decomposition," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2655-2675, June.
  37. Gong, Xu & Lin, Boqiang, 2019. "Modeling stock market volatility using new HAR-type models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 194-211.
  38. Piersanti, Giovanni & Piersanti, Mirko & Cicone, Antonio & Canofari, Paolo & Di Domizio, Marco, 2020. "An inquiry into the structure and dynamics of crude oil price using the fast iterative filtering algorithm," Energy Economics, Elsevier, vol. 92(C).
  39. Julien Chevallier & Bangzhu Zhu & Lyuyuan Zhang, 2021. "Forecasting Inflection Points: Hybrid Methods with Multiscale Machine Learning Algorithms," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 537-575, February.
  40. Ouyang, Fang-Yan & Zheng, Bo & Jiang, Xiong-Fei, 2019. "Dynamic fluctuations of cross-correlations in multi-time scale," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 515-521.
  41. Zhang, Xun & Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2009. "Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method," Energy Economics, Elsevier, vol. 31(5), pages 768-778, September.
  42. Bangzhu Zhu & Xuetao Shi & Julien Chevallier & Ping Wang & Yi‐Ming Wei, 2016. "An Adaptive Multiscale Ensemble Learning Paradigm for Nonstationary and Nonlinear Energy Price Time Series Forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(7), pages 633-651, November.
  43. Anokye M. Adam & Kwabena Kyei & Simiso Moyo & Ryan Gill & Emmanuel N. Gyamfi, 2022. "Multifrequency network for SADC exchange rate markets using EEMD-based DCCA," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(1), pages 145-166, January.
  44. Wu, Yu-Xi & Wu, Qing-Biao & Zhu, Jia-Qi, 2019. "Improved EEMD-based crude oil price forecasting using LSTM networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 114-124.
  45. Yang, Boyu & Sun, Yuying & Wang, Shouyang, 2020. "A novel two-stage approach for cryptocurrency analysis," International Review of Financial Analysis, Elsevier, vol. 72(C).
  46. Ftiti, Zied & Hadhri, Sinda, 2019. "Can economic policy uncertainty, oil prices, and investor sentiment predict Islamic stock returns? A multi-scale perspective," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 40-55.
  47. Chai, Jian & Xing, Li-Min & Zhou, Xiao-Yang & Zhang, Zhe George & Li, Jie-Xun, 2018. "Forecasting the WTI crude oil price by a hybrid-refined method," Energy Economics, Elsevier, vol. 71(C), pages 114-127.
  48. Lin, Boqiang & Su, Tong, 2020. "Does oil price have similar effects on the exchange rates of BRICS?," International Review of Financial Analysis, Elsevier, vol. 69(C).
  49. Lin, Tiantian & Liu, Dehong & Zhang, Lili & Lung, Peter, 2019. "The information content of realized volatility of sector indices in China’s stock market," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 625-640.
  50. Xu, Mengjia & Shang, Pengjian & Lin, Aijing, 2016. "Cross-correlation analysis of stock markets using EMD and EEMD," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 82-90.
  51. Chen, Hao & Liao, Hua & Tang, Bao-Jun & Wei, Yi-Ming, 2016. "Impacts of OPEC's political risk on the international crude oil prices: An empirical analysis based on the SVAR models," Energy Economics, Elsevier, vol. 57(C), pages 42-49.
  52. Lisi, Francesco & Nan, Fany, 2014. "Component estimation for electricity prices: Procedures and comparisons," Energy Economics, Elsevier, vol. 44(C), pages 143-159.
  53. Zhang, Ningning & Lin, Aijing & Shang, Pengjian, 2017. "Multidimensional k-nearest neighbor model based on EEMD for financial time series forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 477(C), pages 161-173.
  54. Oladosu, Gbadebo, 2009. "Identifying the oil price-macroeconomy relationship: An empirical mode decomposition analysis of US data," Energy Policy, Elsevier, vol. 37(12), pages 5417-5426, December.
  55. Sun, Xiaolei & Chen, Xiuwen & Wang, Jun & Li, Jianping, 2020. "Multi-scale interactions between economic policy uncertainty and oil prices in time-frequency domains," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
  56. Tang, Ling & Zhang, Chengyuan & Li, Ling & Wang, Shouyang, 2020. "A multi-scale method for forecasting oil price with multi-factor search engine data," Applied Energy, Elsevier, vol. 257(C).
  57. Ji, Qiang & Geng, Jiang-Bo & Tiwari, Aviral Kumar, 2018. "Information spillovers and connectedness networks in the oil and gas markets," Energy Economics, Elsevier, vol. 75(C), pages 71-84.
  58. Wang, Minggang & Tian, Lixin & Zhou, Peng, 2018. "A novel approach for oil price forecasting based on data fluctuation network," Energy Economics, Elsevier, vol. 71(C), pages 201-212.
  59. Tiwari, Aviral K. & Dar, Arif B. & Bhanja, Niyati & Gupta, Rangan, 2016. "A historical analysis of the US stock price index using empirical mode decomposition over 1791-2015," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 10, pages 1-15.
  60. Guo, Wei & Liu, Qingfu & Luo, Zhidan & Tse, Yiuman, 2022. "Forecasts for international financial series with VMD algorithms," Journal of Asian Economics, Elsevier, vol. 80(C).
  61. Li, Muyi & Huang, Yongxiang, 2014. "Hilbert–Huang Transform based multifractal analysis of China stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 222-229.
  62. Yang, Dongchuan & Guo, Ju-e & Li, Yanzhao & Sun, Shaolong & Wang, Shouyang, 2023. "Short-term load forecasting with an improved dynamic decomposition-reconstruction-ensemble approach," Energy, Elsevier, vol. 263(PA).
  63. Gong, Xingyue & Jia, Guozhu, 2023. "Impactful messaging: Elite sentiment in Chinese new energy vehicle vs machine learning perspective," Finance Research Letters, Elsevier, vol. 57(C).
  64. He, Kaijian & Yu, Lean & Lai, Kin Keung, 2012. "Crude oil price analysis and forecasting using wavelet decomposed ensemble model," Energy, Elsevier, vol. 46(1), pages 564-574.
  65. Jianguo Zhou & Xuechao Yu & Xiaolei Yuan, 2018. "Predicting the Carbon Price Sequence in the Shenzhen Emissions Exchange Using a Multiscale Ensemble Forecasting Model Based on Ensemble Empirical Mode Decomposition," Energies, MDPI, vol. 11(7), pages 1-17, July.
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  67. Zheng, Li & Sun, Yuying & Wang, Shouyang, 2024. "A novel interval-based hybrid framework for crude oil price forecasting and trading," Energy Economics, Elsevier, vol. 130(C).
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