Text-based crude oil price forecasting: A deep learning approach

doi:10.1016/j.ijforecast.2018.07.006

CSpace > 系统科学研究所

	Text-based crude oil price forecasting: A deep learning approach
	Li, Xuerong 1; Shang, Wei1,2 ; Wang, Shouyang1,2
	2019-10-01
发表期刊	INTERNATIONAL JOURNAL OF FORECASTING
ISSN	0169-2070
卷号	35 期号:4 页码:1548-1560
摘要	This study proposes a new, novel crude oil price forecasting method based on online media text mining, with the aim of capturing the more immediate market antecedents of price fluctuations. Specifically, this is an early attempt to apply deep learning techniques to crude oil forecasting, and to extract hidden patterns within online news media using a convolutional neural network (CNN). While the news-text sentiment features and the features extracted by the CNN model reveal significant relationships with the price change, they need to be grouped according to their topics in the price forecasting in order to obtain a greater forecasting accuracy. This study further proposes a feature grouping method based on the Latent Dirichlet Allocation (LDA) topic model for distinguishing effects from various online news topics. Optimized input variable combination is constructed using lag order selection and feature selection methods. Our empirical results suggest that the proposed topic-sentiment synthesis forecasting models perform better than the older benchmark models. In addition, text features and financial features are shown to be complementary in producing more accurate crude oil price forecasts. (C) 2018 The Authors. Published by Elsevier B.V. on behalf of International Institute of Forecasters.
关键词	Oil price forecasting Financial markets Online news Text analysis Convolutional neural network
DOI	10.1016/j.ijforecast.2018.07.006
语种	英语
资助项目	National Natural Science Foundation of China[71571180] ; National Natural Science Foundation of China[71771208] ; National Natural Science Foundation of China[71642006] ; National Center for Mathematics and Interdisciplinary Sciences, CAS
WOS研究方向	Business & Economics
WOS类目	Economics ; Management
WOS记录号	WOS:000490649500028
出版者	ELSEVIER
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/35904
专题	系统科学研究所
通讯作者	Shang, Wei
作者单位	1.Univ Chinese Acad Sci, Sch Econ & Management, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, 55 Zhongguancun East Rd, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Li, Xuerong,Shang, Wei,Wang, Shouyang. Text-based crude oil price forecasting: A deep learning approach[J]. INTERNATIONAL JOURNAL OF FORECASTING,2019,35(4):1548-1560.
APA	Li, Xuerong,Shang, Wei,&Wang, Shouyang.(2019).Text-based crude oil price forecasting: A deep learning approach.INTERNATIONAL JOURNAL OF FORECASTING,35(4),1548-1560.
MLA	Li, Xuerong,et al."Text-based crude oil price forecasting: A deep learning approach".INTERNATIONAL JOURNAL OF FORECASTING 35.4(2019):1548-1560.