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Forecasting crude oil price with multilingual search engine data
Li, Jingjing1; Tang, Ling1; Wang, Shouyang2,3
2020-08-01
Source PublicationPHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
ISSN0378-4371
Volume551Pages:14
AbstractIn the big data era, search engine data (SED) have presented new opportunities for improving crude oil price prediction; however, the existing research were confined to single-language (mostly English) search keywords in SED collection. To address such a language bias and grasp worldwide investor attention, this study proposes a novel multilingual SED-driven forecasting methodology from a global perspective. The proposed methodology includes three main steps: (1) multilingual index construction, based on multilingual SED; (2) relationship investigation, between the multilingual index and crude oil price; and (3) oil price prediction, with the multilingual index as an informative predictor. With WTI spot price as studying samples, the empirical results indicate that SED have a powerful predictive power for crude oil price; nevertheless, multilingual SED statistically demonstrate better performance than single-language SED, in terms of enhancing prediction accuracy and model robustness. (C) 2020 Elsevier B.V. All rights reserved.
KeywordBig data Multilingual search engine index Crude oil price forecasting Google Trends Artificial intelligence
DOI10.1016/j.physa.2020.124178
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[71622011] ; National Natural Science Foundation of China[71971007]
WOS Research AreaPhysics
WOS SubjectPhysics, Multidisciplinary
WOS IDWOS:000534417600038
PublisherELSEVIER
Citation statistics
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/51520
Collection中国科学院数学与系统科学研究院
Corresponding AuthorTang, Ling
Affiliation1.Beihang Univ, Sch Econ & Management, 37 Xueyuan Rd, Beijing 100191, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Sch Econ & Management, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Li, Jingjing,Tang, Ling,Wang, Shouyang. Forecasting crude oil price with multilingual search engine data[J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS,2020,551:14.
APA Li, Jingjing,Tang, Ling,&Wang, Shouyang.(2020).Forecasting crude oil price with multilingual search engine data.PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS,551,14.
MLA Li, Jingjing,et al."Forecasting crude oil price with multilingual search engine data".PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 551(2020):14.
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