Gold Price Forecasting Using Machine Learning Techniques: Review of a Decade

Price of the gold plays a major role in monetary as well as financial systems. Prediction and forecasting the upcoming tendency of gold prices and other valuable metals will be helpful for investors and money managers to evade choosing when to supply this commodity. Central banks throughout the globe uphold gold reserves to assure the currency holders, the money of their shareholders, and foreign-debt creditors. They also utilize the gold treasury as a means to manage inflation and toughen their country’s economic standing. During this procedure, the prediction of the gold rate has become the biggest issue now a days. So, various methods, especially intelligent techniques, have played a vital role in predicting gold prices. Moreover, a comparative investigation on the impact of machine learning (ML) algorithms such as support vector machine (SVM), random forest (RF), linear regression (LR), decision tree (DT), and other hybrid methods for gold price forecasting has been made. Some significant research directions for additional research on gold price prediction are highlighted which may assist the researchers to widen proficient intelligent techniques for the prediction of gold rate.