Machine Learning Approaches for Analyzing Global Metal Trends and Forecasting Prices

Abstract

This work combines economics with modern tools for predictive modeling to examine the complex problem of predicting metal prices. The world of complex supply chains, geopolitical instability and technological advancement is changing quickly, and this has made the need to forecast metal prices much bigger. The results of present study will be useful in assessing the performance of proposed predictive modeling methods for prediction of metal prices. The proposed method provides useful insights in the variables affecting change in prices of metals and helps in predicting the future prices of metals, which is very important for effective management and decision making.