Using Random Forest Algorithm to Improve Investment Decision Making in Damascus Stock Exchange

Abstract

This research aims to explore the potential of using the Random Forest algorithm to improve investment decision-making in the Damascus Stock Exchange. Google Trends data related to key economic indicators were analyzed to develop a predictive model capable of identifying potential investment opportunities and reducing losses. The results demonstrated the algorithm's effectiveness in classifying investment decisions, achieving 62% accuracy in identifying investment opportunities. The analysis also revealed that search patterns for gold prices played a significant role in predicting investment decisions, emphasizing their importance to the Damascus market.