Determining the Best Machine Learning Model by Predicting the Participation Index of the Borsa Istanbul Stock Exchange With Artificial Intelligence

Abstract

Forcasting the future direction of stock indinces has been received significant attention by researchers and investors. Due to the complexcity of information, it is very difficult to predict future stock market price behavior. In this paper, we determine the best machine learning model by forecasting the Borsa Istanbul Stock Exchange participation index with Artificial Intelligence (AI). Six different machine learning algorithms are used to predict the prices of a participation index such as Linear Regression, LSTM, KNN, Auto-ARIMA, Gradient Boosting and Random Forest. Models were built by using the closing rates of the Participation Index between November 2015 and June 2020, and the last 30 days' rate was forecasted. As a main finding, the best model was determined according to accuracy results based on the various models. It is seen that, of the six different machine learning models, the LSTM model provides the most accurate result. This is kind of first study on the prediction of participation index by application of six different machine learning models of AI.