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Interval decomposition ensemble approach for crude oil price forecasting

文献类型：期刊论文

作者Sun, Shaolong1,2,3; Sun, Yuying1,4; Wang, Shouyang1,2,4; Wei, Yunjie1,4
刊名ENERGY ECONOMICS
出版日期2018-10-01
卷号76页码:274-287
关键词Bivariate empirical mode decomposition Crude oil price forecasting Interval-valued time series Interval Holt's method Interval neural networks
ISSN号0140-9883
DOI10.1016/j.eneco.2018.10.015
英文摘要Crude oil is one of the most important energy sources in the world, and it is very important for policymakers, enterprises and investors to forecast the price of crude oil accurately. This paper proposes an interval decomposition ensemble (IDE) learning approach to forecast interval-valued crude oil price by integrating bivariate empirical mode decomposition (BEMD), interval MLP (MLPI) and interval exponential smoothing method (Holt(I)). Firstly, the original interval-valued crude oil price is transformed into a complex-valued signal. Secondly, BEMD is used to decompose the constructed complex-valued signal into a finite number of complex-valued intrinsic mode functions (IMFs) components and one complex-valued residual component. Thirdly, MLPI is used to simultaneously forecast the lower and the upper bounds of each IMF (non-linear patterns), and Holt(I) is used for modeling the residual component (linear pattern). Finally, the forecasting results of the lower and upper bounds of all the components are combined to generate the aggregated interval-valued output by employing another MLPI as the ensemble tool. The empirical results show that our proposed IDE learning approach with different forecasting horizons and different data frequencies significantly outperforms some other benchmark models by means of forecasting accuracy and hypothesis tests. (C) 2018 Elsevier B.V. All rights reserved.
资助项目National Natural Science Foundation of China[71801213] ; National Natural Science Foundation of China[71771208] ; National Natural Science Foundation of China[71642006]
WOS研究方向Business & Economics
语种英语
WOS记录号WOS:000453498400018
出版者ELSEVIER SCIENCE BV
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/31915]  
专题系统科学研究所
通讯作者Wei, Yunjie
作者单位1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Econ & Management, Beijing 100190, Peoples R China
3.City Univ Hong Kong, Sch Data Sci, Kowloon, Tat Chee Ave, Hong Kong, Peoples R China
4.Chinese Acad Sci, Ctr Forecasting Sci, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Sun, Shaolong,Sun, Yuying,Wang, Shouyang,et al. Interval decomposition ensemble approach for crude oil price forecasting[J]. ENERGY ECONOMICS,2018,76:274-287.
APA Sun, Shaolong,Sun, Yuying,Wang, Shouyang,&Wei, Yunjie.(2018).Interval decomposition ensemble approach for crude oil price forecasting.ENERGY ECONOMICS,76,274-287.
MLA Sun, Shaolong,et al."Interval decomposition ensemble approach for crude oil price forecasting".ENERGY ECONOMICS 76(2018):274-287.

入库方式： OAI收割

来源：数学与系统科学研究院

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