A Commonsense Knowledge-Enabled Textual Analysis Approach for Financial Market Surveillance
Li, Xin1; Chen, Kun2; Sun, Sherry X.; Fung, Terrance3; Wang, Huaiqing2; Zeng, Daniel D.4,5
Source PublicationINFORMS JOURNAL ON COMPUTING
2016-03-01
Volume28Issue:2Pages:278-294
SubtypeArticle
AbstractMarket surveillance systems (MSSs) are increasingly used to monitor trading activities in financial markets to maintain market integrity. Existing MSSs primarily focus on statistical analysis of market activity data and largely ignore textual market information, including, but not limited to, news reports and various social media. As suggested by both theoretical explorations in finance and prevailing market surveillance practice, unstructured market information holds major yet underexplored opportunities for surveillance. In this paper, we propose a news analysis approach with the help of commonsense knowledge to assess the risk of suspicious transactions identified in market activity analysis. Our approach explicitly models semantic relations between transactions and news articles and provides semantic references to words in news articles. We conducted experiments using data collected from a real-world market and found that our proposed approach significantly outperforms the existing methods, which are based on transaction characteristics or traditional textual analysis methods. Experiments also show that the performance advantage of the proposed approach mainly comes from the modeling of news-transaction relationships. The research contributes to the market surveillance literature and has significant practical implications.
KeywordMarket Surveillance Text Mining Commonsense Knowledge Business Intelligence Intelligent Financial Systems
WOS HeadingsScience & Technology ; Technology
DOI10.1287/ijoc.2015.0677
WOS KeywordQUERY EXPANSION ; INVESTOR SENTIMENT ; MODEL ; INFORMATION ; LANGUAGE ; WORDNET ; SYSTEM ; TALK ; WEB
Indexed BySCI ; SSCI
Language英语
Funding OrganizationCity University of Hong Kong(SRG 7002898 ; NNSFC(71025001 ; GuangDong NSF(2015A030313876) ; Shenzhen Foundation Research(JCYJ20140417105742712) ; SRG 7004142) ; 71572169)
WOS Research AreaComputer Science ; Operations Research & Management Science
WOS SubjectComputer Science, Interdisciplinary Applications ; Operations Research & Management Science
WOS IDWOS:000377110200007
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12181
Collection复杂系统管理与控制国家重点实验室_互联网大数据与信息安全
Affiliation1.City Univ Hong Kong, Coll Business, Dept Informat Syst, Hong Kong, Hong Kong, Peoples R China
2.South Univ Sci & Technol China, Dept Finance, Shenzhen 518000, Guangdong, Peoples R China
3.Secur & Futures Commiss Hong Kong, Hong Kong, Hong Kong, Peoples R China
4.Chinese Acad Sci, Inst Automat, Beijing 100864, Peoples R China
5.Univ Arizona, Dept Management Informat Syst, Tucson, AZ 85721 USA
Recommended Citation
GB/T 7714
Li, Xin,Chen, Kun,Sun, Sherry X.,et al. A Commonsense Knowledge-Enabled Textual Analysis Approach for Financial Market Surveillance[J]. INFORMS JOURNAL ON COMPUTING,2016,28(2):278-294.
APA Li, Xin,Chen, Kun,Sun, Sherry X.,Fung, Terrance,Wang, Huaiqing,&Zeng, Daniel D..(2016).A Commonsense Knowledge-Enabled Textual Analysis Approach for Financial Market Surveillance.INFORMS JOURNAL ON COMPUTING,28(2),278-294.
MLA Li, Xin,et al."A Commonsense Knowledge-Enabled Textual Analysis Approach for Financial Market Surveillance".INFORMS JOURNAL ON COMPUTING 28.2(2016):278-294.
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