Using machine learning and deep learning methods in predicting the islamic index price

Abstract

In recent years, there has been a noticeable surge in the popularity of Islamic financing. The utilization of Fin-Tech tools assumes significance for investors adhering to Islamic principles in order to effectively navigate investing choices. The utilization of these technologies enables the generation of more precise price forecasts for investors. This will facilitate investors adhering to Islamic principles in making more precise investing choices. This study utilized a dataset consisting of 3453 daily observations of the MSCI ACWI Islamic Index. The acquired data was subjected to processing utilizing various machine learning algorithms, including LSTM, CNN, GRU, RF, and XGBoost. Subsequently, an evaluation was conducted to ascertain the predictive performance of each method and establish the superior approach. Based on the results, it was found that the GRU approach exhibited the highest level of prediction performance. © 2024, IGI Global. All rights reserved.