Apply big data analytics for forecasting the prices of precious metals futures to construct a hedging strategy for industrial material procurement

Abstract

This study explores the critical factors affecting the prices of precious metals by using Granger causality tests through collecting financial market information and network traffic volume of Google Trend keywords and the traditional financial index. It establishes a forecasting model of precious metal price to assist the procurement of precious metals as raw materials which help to reduce material costs and control risks, thus lifting a company's profits. The results reveal that the prices of precious metals have a causality relation with their own exchange‐traded funds, US 10‐year treasury rate, and the Dow Jones Industrial Average but not Google Trends.