Stock Market Prediction with Deep Learning Using Public Disclosure Platform Data
Bildiriler > Tam Metin Bildiri · 2020
Yazarlar: Büşra Aslan, Rıza Cenk ERDUR
Akıllı Sistemlerde Yenilikler ve Uygulamaları (ASYU 2020), Türkiye, İstanbul, Uluslararası, Sözlü Sunum, Tam Metin Bildiri, 2020-2020, ss 1-5
DOI: 10.1109/asyu50717.2020.9259836
Özet
Prediction of a company’s stock value is one of the most important encountered problems in Stock Markets. In this study, stock value prediction has been made for the three sport clubs Galatasaray (GSRAY), Fenerbahçe (FENER) and Beşiktaş (BJKAS) that have stock values in Borsa Istanbul. Sentiment analysis results that have been obtained using the Public Disclosure Platform notification data about GSRAY, FENER and BJKAS have been used in addition to financial data that belong to these companies for stock market prediction. Long-short term memory, which is one of the deep learning methods, has been used for prediction. According to experimental results, when Public Disclosure Platform notification data about these companies have been used in prediction, the prediction results are more accurate.