Text-based crude oil price forecasting: A deep learning approach
文献类型：期刊论文
| 作者 | Li, Xuerong1; Shang, Wei1,2 ; Wang, Shouyang1,2
|
| 刊名 | INTERNATIONAL JOURNAL OF FORECASTING
 |
| 出版日期 | 2019-10-01 |
| 卷号 | 35期号:4页码:1548-1560 |
| ISSN号 | 0169-2070 |
| 关键词 | Oil price forecasting Financial markets Online news Text analysis Convolutional neural network |
| DOI | 10.1016/j.ijforecast.2018.07.006 |
| 英文摘要 | 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. |
| 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 |
| 语种 | 英语 |
| 出版者 | ELSEVIER |
| WOS记录号 | WOS:000490649500028 |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/35903]  |
| 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. |
入库方式： OAI收割
来源：数学与系统科学研究院
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