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Analysis of price models in istanbul stock exchange, Borsa istanbul hisse senedi fiyat modelleri analizi

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dc.contributor.authorTekin, Sefa
dc.contributor.authorÇanakoǧlu, Ethem
dc.contributor.institutionTekin, Sefa, Bilgisayar Mühendisliǧi Bölümü, Bahçeşehir Üniversitesi, Istanbul, Turkey
dc.contributor.institutionÇanakoǧlu, Ethem, Bilgisayar Mühendisliǧi Bölümü, Bahçeşehir Üniversitesi, Istanbul, Turkey
dc.date.accessioned2025-10-05T16:00:12Z
dc.date.issued2019
dc.description.abstractEquity investments are one of the most important asset classes. Equity investments have high return yield however also high risk due to the variability of share prices. Therefore, precise share price modeling is essential. In this study, we examined the data of 30 leading companies of Borsa Ë™Istanbul. We applied ARIMA, Machine learning algorithms and Deep learning techniques (LSTM) to BIST30 stock prices. As a result of the computational analysis, we observed that ARIMA performs better than LSTM and linear regression performs better than other machine learning techniques. © 2020 Elsevier B.V., All rights reserved.
dc.identifier.conferenceName27th Signal Processing and Communications Applications Conference, SIU 2019
dc.identifier.conferencePlaceSivas
dc.identifier.doi10.1109/SIU.2019.8806296
dc.identifier.isbn9781728119045
dc.identifier.scopus2-s2.0-85071974938
dc.identifier.urihttps://doi.org/10.1109/SIU.2019.8806296
dc.identifier.urihttps://hdl.handle.net/20.500.14719/11150
dc.language.isotr
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subject.authorkeywordsArima
dc.subject.authorkeywordsBi̇st30
dc.subject.authorkeywordsDeep Learning
dc.subject.authorkeywordsMachine Learning
dc.subject.authorkeywordsStock Returns
dc.subject.authorkeywordsİstanbul Stock Exchange
dc.subject.authorkeywordsCosts
dc.subject.authorkeywordsDeep Learning
dc.subject.authorkeywordsFinancial Markets
dc.subject.authorkeywordsInvestments
dc.subject.authorkeywordsLearning Algorithms
dc.subject.authorkeywordsLearning Systems
dc.subject.authorkeywordsMachine Learning
dc.subject.authorkeywordsSignal Processing
dc.subject.authorkeywordsArima
dc.subject.authorkeywordsComputational Analysis
dc.subject.authorkeywordsEquity Investment
dc.subject.authorkeywordsIstanbul Stock Exchange
dc.subject.authorkeywordsLearning Techniques
dc.subject.authorkeywordsMachine Learning Techniques
dc.subject.authorkeywordsStock Exchange
dc.subject.authorkeywordsStock Returns
dc.subject.authorkeywordsLong Short-term Memory
dc.subject.indexkeywordsCosts
dc.subject.indexkeywordsDeep learning
dc.subject.indexkeywordsFinancial markets
dc.subject.indexkeywordsInvestments
dc.subject.indexkeywordsLearning algorithms
dc.subject.indexkeywordsLearning systems
dc.subject.indexkeywordsMachine learning
dc.subject.indexkeywordsSignal processing
dc.subject.indexkeywordsARIMA
dc.subject.indexkeywordsComputational analysis
dc.subject.indexkeywordsEquity investment
dc.subject.indexkeywordsIstanbul stock exchange
dc.subject.indexkeywordsLearning techniques
dc.subject.indexkeywordsMachine learning techniques
dc.subject.indexkeywordsStock exchange
dc.subject.indexkeywordsStock returns
dc.subject.indexkeywordsLong short-term memory
dc.titleAnalysis of price models in istanbul stock exchange, Borsa istanbul hisse senedi fiyat modelleri analizi
dc.typeConference Paper
dcterms.referencesBoyacioglu, Melek Acar, An adaptive network-based fuzzy inference system (ANFIS) for the prediction of stock market return: The case of the Istanbul stock exchange, Expert Systems with Applications, 37, 12, pp. 7908-7912, (2010), Ahmad, Saif A., Summarizing time series: Learning patterns in 'volatile' series, Lecture Notes in Computer Science, 3177, pp. 523-532, (2004), Huang, Wei, Forecasting stock market movement direction with support vector machine, Computers and Operations Research, 32, 10, pp. 2513-2522, (2005), Journal of Business, (1965), Solakoĝlu, Mehmet Nihat, Sentimental herding in Borsa Istanbul: informed versus uninformed, Applied Economics Letters, 21, 14, pp. 965-968, (2014), Adebiyi, Ayodele Ariyo, Stock price prediction using the ARIMA model, pp. 106-112, (2014), Business Intelligence Journal, (2010), Time Series Analysis Forecasting and Control, (1976), Forecasting Economics and Financial Time Series Arima Vs Lstm, (2018), Box Jenkins Modelleri Ile Aylik Doviz Kuru Tahmini Uzerine Bir Uygulama, (2003)
dspace.entity.typePublication
local.indexed.atScopus
person.identifier.scopus-author-id57203172532
person.identifier.scopus-author-id15047450100

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