Stock Closing Price Prediction with Machine Learning Algorithms: PETKM Stock Example In BIST

Authors : Şevval TOPRAK, Gültekin ÇAĞIL, Abdullah Hulusi KÖKÇAM

Pages : 958-976

Doi:10.29130/dubited.1096767

View : 13 | Download : 5

Publication Date : 2023-04-30

Article Type : Research Paper

Abstract :This study predicts the stock price of Petkim Petrokimya Holding Corp. insert ignore into journalissuearticles values(PETKM);, which is listed in Borsa Istanbul insert ignore into journalissuearticles values(BIST);, using PETKM stock price, US dollar insert ignore into journalissuearticles values(USD/TRY); price and BIST Chemical, Petroleum & Plastic insert ignore into journalissuearticles values(XKMYA); index price. A time series data set with three inputs and one output is created using these data. Random Forest Regression insert ignore into journalissuearticles values(RFR);, Long-Short Term Memory insert ignore into journalissuearticles values(LSTM);, and Convolutional Neural Network insert ignore into journalissuearticles values(CNN); algorithms are used in the prediction model. The success of these methods is compared using performance metrics such as MSE, RMSE, MAE, and R2. According to the calculated error metrics, LSTM and RFR algorithms gave better results than CNN with an MSE value less than 0.02. However, the fact that the R2 values of the most successful models created with all three algorithms were greater than 95% revealed that all the algorithms mentioned could be used to estimate this data set.
Keywords : Hisse senedi fiyat tahmini, Makine öğrenmesi, Derin öğrenme, RFR, LSTM