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Predicting the listing statuses of Chinese-listed companies using decision trees combined with an improved filter feature selection method
Ligang Zhou1; Yain-Whar Si2; Hamido Fujita3
2017-07-15
Source PublicationKNOWLEDGE-BASED SYSTEMS
ISSN0950-7051
Volume128Pages:93-101
Abstract

Predicting the listing statuses of Chinese-listed companies (PLSCLC) is an important and complex problem for investors in China. There is a large quantity of information related to each company's listing status. We propose an improved filter feature selection method to select effective features for predicting the listing statuses of Chinese-listed companies. Due to the practical concerns of analysts in finance about the performance and interpretability of the prediction models, models based on decision trees C4.5 and C5.0 are employed and are compared with several other widely used models. To evaluate the models' robustness with time, the models are also tested under rolling time windows. The empirical results demonstrate the efficacy of the proposed feature selection method and decision tree C5.0 model. (C) 2017 Elsevier B.V. All rights reserved.

KeywordMulti-class Classification Listing-status Prediction Decision Tree C4.5 Decision Tree C5.0
DOI10.1016/j.knosys.2017.05.003
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000403633500008
PublisherELSEVIER SCIENCE BV
The Source to ArticleWOS
Fulltext Access
Citation statistics
Cited Times [WOS]:9   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorLigang Zhou; Yain-Whar Si; Hamido Fujita
Affiliation1.School of Business, Macau University of Science and Technology, Taipa, Macau
2.Department of Computer and Information Science, University of Macau, Macau
3.Faculty of Software and Information Science, Iwate Prefectural University, Iwate, Japan
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Ligang Zhou,Yain-Whar Si,Hamido Fujita. Predicting the listing statuses of Chinese-listed companies using decision trees combined with an improved filter feature selection method[J]. KNOWLEDGE-BASED SYSTEMS,2017,128:93-101.
APA Ligang Zhou,Yain-Whar Si,&Hamido Fujita.(2017).Predicting the listing statuses of Chinese-listed companies using decision trees combined with an improved filter feature selection method.KNOWLEDGE-BASED SYSTEMS,128,93-101.
MLA Ligang Zhou,et al."Predicting the listing statuses of Chinese-listed companies using decision trees combined with an improved filter feature selection method".KNOWLEDGE-BASED SYSTEMS 128(2017):93-101.
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