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

被引：2

作者：

Li, Sheng-Tun ^{[1
,2
]}

Chiu, Kuei-Chen ^{[3
]}

Wu, Chien-Chang ^{[4
]}

机构：

[1] Natl Cheng Kung Univ, Ctr Innovat FinTech Business Models, Tainan, Taiwan

[2] Natl Cheng Kung Univ, Coll Management, Dept Ind & Informat Management, Tainan, Taiwan

[3] Shih Chien Univ, Dept Finance, 200 Univ Rd, Kaohsiung, Taiwan

[4] Adv Elect Mat Inc, Tainan, Taiwan

来源：

MANAGERIAL AND DECISION ECONOMICS | 2023年 / 44卷 / 02期

关键词：

TIME-SERIES; UNIT-ROOT; CRUDE-OIL; MACROECONOMIC VARIABLES; GOLD; SENTIMENT; RETURNS; BITCOIN; MODELS; MARKET;

D O I：

10.1002/mde.3723

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

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.

引用

页码：942 / 959

页数：18