Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11851/6511
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ögüt, Hulisi | - |
dc.contributor.author | Doğanay, M. Mete | - |
dc.contributor.author | Aktaş, Ramazan | - |
dc.date.accessioned | 2021-09-11T15:37:02Z | - |
dc.date.available | 2021-09-11T15:37:02Z | - |
dc.date.issued | 2009 | en_US |
dc.identifier.issn | 0957-4174 | - |
dc.identifier.uri | https://doi.org/10.1016/j.eswa.2009.03.065 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.11851/6511 | - |
dc.description.abstract | This paper aims to develop methods that are capable of detecting manipulation in the Istanbul Stock Exchange. We take the difference between manipulated stock's and index's average daily return, average daily change in trading volume and average daily volatility and used these statistics as explanatory variables. The data in post-manipulation and pre-manipulation periods are used as non-manipulated instances while the data in the manipulation period are used as manipulated instances. Test performance of classification accuracy, sensitivity and specificity statistics for Artificial Neural Networks (ANN) and Support Vector Machine (SVM) are compared with the results of discriminant analysis and logistics regression (logit). We found that the data mining techniques (ANN and SVM) are better suited to detect stock-price manipulation than multivariate statistical techniques (discriminant analysis, logistics regression) as the performances of the data mining techniques in terms of total classification accuracy and sensitivity statistics are better than those of multivariate techniques. We also found that unit change in difference between average daily return of manipulated stock and the index has the largest effect while unit change in difference between average daily change in trading volume of manipulated stock and index has the least effect on multivariate classifiers' decision functions. (C) 2009 Elsevier Ltd. All rights reserved. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Pergamon-Elsevier Science Ltd | en_US |
dc.relation.ispartof | Expert Systems With Applications | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Stock market | en_US |
dc.subject | Manipulation | en_US |
dc.subject | Data mining techniques | en_US |
dc.subject | Multivariate statistical techniques | en_US |
dc.title | Detecting Stock-Price Manipulation in an Emerging Market: the Case of Turkey | en_US |
dc.type | Article | en_US |
dc.department | Faculties, Faculty of Economics and Administrative Sciences, Department of Management | en_US |
dc.department | Fakülteler, İktisadi ve İdari Bilimler Fakültesi, İşletme Bölümü | tr_TR |
dc.identifier.volume | 36 | en_US |
dc.identifier.issue | 9 | en_US |
dc.identifier.startpage | 11944 | en_US |
dc.identifier.endpage | 11949 | en_US |
dc.identifier.wos | WOS:000268270600060 | en_US |
dc.identifier.scopus | 2-s2.0-67349175047 | en_US |
dc.institutionauthor | Aktaş, Ramazan | - |
dc.identifier.doi | 10.1016/j.eswa.2009.03.065 | - |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopusquality | Q1 | - |
item.openairetype | Article | - |
item.languageiso639-1 | en | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
crisitem.author.dept | 04.03. Department of Management | - |
Appears in Collections: | İşletme Bölümü / Department of Management Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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