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Research on gold price prediction based on ARIMA model
- 1 College of Science, Civil Aviation University of China, Tianjin, 300300, China
* Author to whom correspondence should be addressed.
Abstract
Gold is one of the most prevalent currencies in the world and its price has a very strong influence in the global financial markets. Gold has safe-haven properties, which can have a significant impact on its demand and price, especially in times of social unrest or financial crisis. Now, the demand for gold by investors has increased dramatically. Therefore, being able to accurately predict the direction of the gold price can help investors to effectively develop investment strategies and risk management measures. The overall objective of this study is to forecast the price of gold futures for the next six months. In this study, the Kaggle website was searched to find the price of gold from 2020 to 2024 and finally the CLOSE price was chosen as the final predicted price. This paper uses the ARIMA model for gold price forecasting. By comparing the RSME size of each model, ARIMA (1, 1, 2) is finally chosen. From the prediction results the price of gold remains stable in the first half of the year and then increases significantly. From the results of the residual test, there is no autocorrelation, and then it is white noise.
Keywords
Gold, ARIMA, autocorrelation, prediction
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Cite this article
Bai,Y. (2024). Research on gold price prediction based on ARIMA model. Theoretical and Natural Science,52,41-48.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of CONF-MPCS 2024 Workshop: Quantum Machine Learning: Bridging Quantum Physics and Computational Simulations
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