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dc.contributor.authorAndreou, Andreas S.en
dc.contributor.authorNeocleous, Constantinos C.en
dc.contributor.authorSchizas, Christos N.en
dc.contributor.authorToumpouris, Costasen
dc.creatorAndreou, Andreas S.en
dc.creatorNeocleous, Constantinos C.en
dc.creatorSchizas, Christos N.en
dc.creatorToumpouris, Costasen
dc.description.abstractA systematic investigation of the effect of different neural network architecture alternatives for predicting the future course of stock prices in the Cyprus Stock Exchange (CSE) market is conducted. This market exhibited an abrupt increase in the general index price during the last year, thus forming a very interesting case for research purposes. The influence of various economic and political factors, from both the local and the international scene, have also been examined. The main conclusion drawn is that the CSE market is governed by unique conditions which when properly modeled can yield successful predictions.en
dc.sourceProceedings of the International Joint Conference on Neural Networksen
dc.sourceInternational Joint Conference on Neural Networks (IJCNN'2000)en
dc.subjectMathematical modelsen
dc.subjectRisk managementen
dc.subjectIndustrial economicsen
dc.subjectNeural networksen
dc.subjectStock pricesen
dc.titleTesting the predictability of the Cyprus Stock Exchange: The case of an emerging marketen
dc.description.endingpage365 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied SciencesΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeConference Objecten
dc.description.notes<p>Sponsors: IEEE Neural Network Councilen
dc.description.notesInternational Neural Network Societyen
dc.description.notesEuropean Neural Network Societyen
dc.description.notesConference code: 57397en
dc.description.notesCited By :6</p>en
dc.contributor.orcidSchizas, Christos N. [0000-0001-6548-4980]
dc.contributor.orcidAndreou, Andreas S. [0000-0001-7104-2097]

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