The role of news sentiment in oil futures returns and volatility forecasting: Data-decomposition based deep learning approach

doi:10.1016/j.eneco.2021.105140

	The role of news sentiment in oil futures returns and volatility forecasting: Data-decomposition based deep learning approach
	Li, Yuze 1,3; Jiang, Shangrong 2; Li, Xuerong 1; Wang, Shouyang 1,2
刊名	ENERGY ECONOMICS
	2021-03-01
卷号	95 页码:11
关键词	News sentiment Returns and volatility forecasting Variational mode decomposition Deep learning
ISSN号	0140-9883
DOI	10.1016/j.eneco.2021.105140
英文摘要	In this paper, we extract the qualitative information from crude oil news headlines, and develop a novel VMDBiLSTM model with investor sentiment indicator for crude oil forecasting. First, we construct a sentiment score considering cumulative effect from contextual data of oil news texts. Then, we adopt an event-based method and GARCH model to investigate the impact of news sentiment on returns and volatility. A non-recursive signal decomposition method, namely variational mode decomposition (VMD), is applied to decompose the historical crude oil return and volatility data into various intrinsic modes. After that, a bidirectional long short-term memory neural networks (BiLSTM) is introduced as the deep learning prediction model that integrates both the qualitative and quantitative model inputs. Our empirical results indicate that the shock of news sentiment significantly causes the fluctuation of oil futures prices, and news sentiment has an asymmetric impact on the volatility of oil futures. The incorporation of sentiment score is always helpful for improving the forecasting performances in all benchmark scenarios. Specifically, our proposed data-decomposition based deep learning model is more effective than several econometric and machine learning models. (c) 2021 Elsevier B.V. All rights reserved.
资助项目	National Natural Science Foundation of China[71901205]
WOS研究方向	Business & Economics
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000625365400012
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/58324]
专题	中国科学院数学与系统科学研究院
通讯作者	Li, Xuerong
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, 55th Zhongguancun East Rd, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Econ & Management, Beijing 100049, Peoples R China 3.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Li, Yuze,Jiang, Shangrong,Li, Xuerong,et al. The role of news sentiment in oil futures returns and volatility forecasting: Data-decomposition based deep learning approach[J]. ENERGY ECONOMICS,2021,95:11.
APA	Li, Yuze,Jiang, Shangrong,Li, Xuerong,&Wang, Shouyang.(2021).The role of news sentiment in oil futures returns and volatility forecasting: Data-decomposition based deep learning approach.ENERGY ECONOMICS,95,11.
MLA	Li, Yuze,et al."The role of news sentiment in oil futures returns and volatility forecasting: Data-decomposition based deep learning approach".ENERGY ECONOMICS 95(2021):11.