Iron Ore Price Prediction Based on Multiple Linear Regression Model

Author:

Wang Yanyi123ORCID,Guo Zhenwei123ORCID,Zhang Yunrui4,Hu Xiangping5ORCID,Xiao Jianping123

Affiliation:

1. School of Geosciences and Info-Physics, Central South University, Changsha 410083, China

2. Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, (Central South University), Ministry of Education, Changsha 410083, China

3. Hunan Key Laboratory of Nonferrous Resources and Geological Hazard Exploration, Changsha 410083, China

4. ESSEC Business School, 95021 Paris, France

5. Industrial Ecology Programme and Department of Energy and Process Engineering, Norwegian University of Science and Technology (NTNU), 7034 Trondheim, Norway

Abstract

The fluctuation of iron ore prices is one of the most important factors affecting policy. Therefore, the accurate prediction of iron ore prices has significant value in analysis and judgment regarding future changes in policies. In this study, we propose a correlation analysis to extract eight influencing factors of iron ore prices and introduce multiple linear regression analysis to the prediction. With historical data, we establish a model to forecast iron ore prices from 2020 to 2024. Taking prices in 2018 and 2019 as samples to test the applicability of the model, we obtain an acceptable level of error between the predicted iron ore prices and the actual prices. The prediction model based on multiple linear regression has high prediction accuracy. Iron ore prices will show a relatively stable upward trend over the next five years without the effects of COVID-19.

Funder

Basic Science Center Project National Natural Science Foundation of China

Hunan Science and Technology Major Project of the Ministry of Science and Technology of China

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

Reference37 articles.

1. Global trends in reserves, production and utilization of iron ore and its sustainability with special emphasis to India;Mishra;J. Mines Met. Fuels,2020

2. Evolution of iron ore prices;Astier;Miner. Econ.,2015

3. Iron Ore Resources: Their Conservation, Value addition and Impact on Iron and Steel Industry;Upadhyay;Tata Search,2008

4. The transmission effects of iron ore price shocks on China’s economy and industries: A CGE approach;Wang;Int. J. Trade Glob. Mark.,2007

5. Do iron ore price bubbles occur?;Su;Resour. Policy,2017

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