How effective is machine learning in stock market predictions?

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dc.authoridAYYILDIZ, Nazif/0000-0002-7364-8436
dc.authoridIskenderoglu, Omer/0000-0002-3407-1259
dc.contributor.authorAyyildiz, Nazif
dc.contributor.authorIskenderoglu, Omer
dc.date.accessioned2024-11-07T13:31:46Z
dc.date.available2024-11-07T13:31:46Z
dc.date.issued2024
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description.abstractIn this study, it is aimed to compare the performances of the algorithms by predicting the movement directions of stock market indexes in developed countries by employing machine learning algorithms (MLMs) and determining the best estimation algorithm. For this purpose, the movement directions of indexes such as the NYSE 100 (the USA), NIKKEI 225 (Japan), FTSE 100 (the UK), CAC 40 (France), DAX 30 (Germany), FTSE MIB (Italy), and TSX (Canada) were estimated by employing the decision tree, random forest k -nearest neighbor, naive Bayes, logistic regression, support vector machines and artificial neural network algorithms. According to the results obtained, artificial neural networks were found to be the best algorithm for NYSE 100, FTSE 100, DAX 30 and FTSE MIB indices, while logistic regression was determined to be the best algorithm for the NIKKEI 225, CAC 40, and TSX indices. The artificial neural networks, which exhibited the highest average prediction performance, have been determined as the best prediction algorithm for the stock market indices of developed countries. It was also noted that artificial neural networks, logistic regression, and support vector machines algorithms were capable of predicting the directional movements of all indices with an accuracy rate of over 70 %.
dc.identifier.doi10.1016/j.heliyon.2024.e24123
dc.identifier.issn2405-8440
dc.identifier.issue2
dc.identifier.pmid38293519
dc.identifier.scopus2-s2.0-85182565802
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.heliyon.2024.e24123
dc.identifier.urihttps://hdl.handle.net/11480/15039
dc.identifier.volume10
dc.identifier.wosWOS:001163934400001
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherCell Press
dc.relation.ispartofHeliyon
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241106
dc.subjectFinancial analysis
dc.subjectMachine learning
dc.subjectClassification algorithms
dc.subjectStock market indexes
dc.titleHow effective is machine learning in stock market predictions?
dc.typeArticle

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