A Stock Market Prediction System, utilizing a combination of data mining algorithms on “gvol-candlesticks”© patterns and neural networks focused on an input smart pre-process system using technical indicators.

dc.contributor.advisor	Liolios, Nikolaos	en
dc.creator	Goumatianos, Nikitas	en
dc.date.accessioned	2020-07-12T09:23:47Z
dc.date.available	2020-07-12T09:23:47Z
dc.date.issued	2008
dc.identifier.other	20941
dc.identifier.uri	http://hdl.handle.net/11615/52911
dc.identifier.uri	http://dx.doi.org/10.26253/heal.uth.8873
dc.description.abstract	The dissertation explores aspects and methods beyond technical analysis hoping to bring successful results in the stock market. Actually, it involves two different scientific approaches. The one approach is to discover unknown patterns that can be used fo	en
dc.language.iso	en	en
dc.rights	Attribution-NonCommercial-NoDerivatives 4.0 International	en
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	en
dc.subject	data mining	en
dc.subject	algorithms	en
dc.subject	neural networks	en
dc.title	A Stock Market Prediction System, utilizing a combination of data mining algorithms on “gvol-candlesticks”© patterns and neural networks focused on an input smart pre-process system using technical indicators.	en
dc.type	masterThesis	en
heal.recordProvider	Πανεπιστήμιο Θεσσαλίας - Βιβλιοθήκη και Κέντρο Πληροφόρησης	el
heal.academicPublisher	ΤΕΙ Θεσσαλίας. Τμήμα Μηχανικών Πληροφορικής T.E.	el
heal.academicPublisherID	teilar
heal.fullTextAvailability	TRUE	en
dc.rights.accessRights	free	en

Excepté là où spécifié autrement, la license de ce document est décrite en tant que Attribution-NonCommercial-NoDerivatives 4.0 International