Elliot Waves Predicting for Stock Marketing Using Euclidean Based Normalization Method Merged with Artificial Neural Network

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dc.contributor.authorAkdemir, Bayram
dc.contributor.authorYu, Lingwen
dc.date.accessioned2020-03-26T17:38:33Z
dc.date.available2020-03-26T17:38:33Z
dc.date.issued2009
dc.departmentSelçuk Üniversitesien_US
dc.description4th International Conference on Computer Sciences and Convergence Information Technology -- NOV 24-26, 2009 -- Seoul, SOUTH KOREAen_US
dc.description.abstractFinancial Marketing is very common in the world to make money or to control the company strategy. Nearly all events trigger to each other and moreover countries. Some predicting methods, on guessing the marketing depends on natural behavior of the events. When, have a scrutinize to backwards, it can be evaluated that some upfront events occur periodically and trigger to each others and may lead to next known moving. Elliot is one of the famous estimating methods on stock marketing. Elliot waves let to time to think and analyze the next moving not in hurry. The proposed method consist of three stages (i) arranging the real time data (ii) data normalization according to Euclidean distance named Euclidean Based Normalization Method and (iii) performing artificial neural network to predict the next swing of the stock or financial marketing. The results compared raw data results and minimum maximum normalization methods to EBNM. Mean squared error and Average Deviation and R-2 statistical value were used as performance criteria. According to MSE, the obtained results were 0.000484, 0.205069 and 0.003178 minimum maximum normalization, raw data set and EBNM method respectively. The performance of the proposed method has more accurate than the other two methods.en_US
dc.description.sponsorshipIEEEen_US
dc.identifier.doi10.1109/ICCIT.2009.296en_US
dc.identifier.endpage+en_US
dc.identifier.isbn978-1-4244-5244-6
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage562en_US
dc.identifier.urihttps://dx.doi.org/10.1109/ICCIT.2009.296
dc.identifier.urihttps://hdl.handle.net/20.500.12395/23510
dc.identifier.wosWOS:000280705700112en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofICCIT: 2009 FOURTH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCES AND CONVERGENCE INFORMATION TECHNOLOGY, VOLS 1 AND 2en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectArtificial neural networken_US
dc.subjectEuclidean distanceen_US
dc.subjectElliot wavesen_US
dc.subjectnormalizationen_US
dc.subjectfinancial marketingen_US
dc.titleElliot Waves Predicting for Stock Marketing Using Euclidean Based Normalization Method Merged with Artificial Neural Networken_US
dc.typeConference Objecten_US

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