Author(s): Kaoutar Abbahaddou, Mohammed Salah Chiadmi
This article analyzes the performance of Machine Learning models in the prediction of stock market indices returns. The empirical study is based on the case of Islamic stock market. The accuracy rate will be the tool used to measure the ability of the models to predict the next price and sharpe ratio will be used to evaluate the performance. As a result of this study, we can say that support vector machine (SVM) outperforms other models namely CART, RF and ANN.