Theoretical and Natural Science

- The Open Access Proceedings Series for Conferences


Theoretical and Natural Science

Vol. 2, 20 February 2023

Open Access | Article

Predict Gold Price Trend Based on ARIMA Model

D L Gao * 1 , J Y Liang 2 , B H Xu 3
1 School of Mathematical and Statistical Sciences, Ludong University, Yantai, Shandong 264011(post), China
2 School of Information and Computing Sciences, Jinan University, Guangzhou, Guangdong 511436(post), China
3 School of Mathematics and Applied Mathematics, Sun Yat-sen University, Guangzhou, Guangdong 510275(post), China

* Author to whom correspondence should be addressed.

Advances in Humanities Research, Vol. 2, 157-165
Published 20 February 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation D L Gao, J Y Liang, B H Xu. Predict Gold Price Trend Based on ARIMA Model. TNS (2023) Vol. 2: 157-165. DOI: 10.54254/2753-8818/2/20220127.

Abstract

As a financial product, gold is one of the more important spot and futures trading products in the commodity market. Based on the time series model, the gold price can be fitted and predicted, in order to explore the law of gold price changes. It has positive implications for investors and government managers. This article selects the Prime Day price in 2018 as the research object. Combined with domestic and foreign research content on financial time series. First, through the time series diagram test and the unit root test, it is obtained that the gold daily price series is a cycle-free and non-stationary series. Therefore, the time series needs to be differentiated. Second, a new stationary sequence is obtained by making second-order differences. Third, after the time sequence diagram test, ADF test, and white noise test, the sequence is a non-white noise sequence. Comparing the AIC values of multiple time series models, the most ideal model for the series should be the ARIMA (2,2,2) model. The significance test of the model shows that the fitted model is significantly effective. And the significance test of the model parameters is also passed. Then make predictions with this model. Comparing the predicted value with the future real gold price, it is found that the predicted value is close to the real value. This is a good reference for the country to formulate relevant economic policies.

Keywords

significance test, ARIMA model, white noise test, gold price, time series

References

1. Zou Q 2014 Research on the Financial Function of Gold (Shanghai: Shanghai Academy of Social Sciences)

2. Duan H 2021 Research on Gold Futures Price Prediction Based on Time Series (Harbin: Harbin Institute of Technology)

3. Ou H 2016 Statistical Analysis and Prediction of Gold Price (Fijian: Fujian Normal University).

4. Xie C, Qu M and Wang G 2013 Study on the Optimal Hedging Ratio of Gold Market Based on M-Copula-GJR-VAR Model (Management science) 26(02) pp 90-99

5. Chen X, Tian L and Han X 2018 Gold price forecast analysis and research. Journal of Foshan University of Science and Technology (Natural Science Edition) 36(04) pp 6-10

6. Cao X 2017 Gold Price Prediction Model and Parameter Optimization Based on SVM (Shandong: Shandong University)

7. Cheng M 2020 Research on Forecasting Method of International Gold Price (Shandong: Shandong University)

8. Chen Xu 2015 Application of Time Series in Gold Price Forecasting Business 2015(16) pp 180-181

9. Wang Y 2010 Research on Gold Price Forecast Based on Variable Coefficient Regression Model (Tianjin: Tianjin University)

10. Pan X 2020 Empirical Analysis of Gold Price Based on ARIMA-GARCH Model Business 2020 (20) pp 155-156

11. Chen Y 2013 Can Gold Hold its Value with Volatile Prices? NCNA 2013-05-03(006)

12. Yin L and Liu Y 2015 Is Gold a Stable Haven? —— From the Perspective of Macroeconomic Uncertainty International Financial Studies 2015(07) pp 87-96

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 the International Conference on Computing Innovation and Applied Physics (CONF-CIAP 2022)
ISBN (Print)
978-1-915371-13-3
ISBN (Online)
978-1-915371-14-0
Published Date
20 February 2023
Series
Theoretical and Natural Science
ISSN (Print)
2753-8818
ISSN (Online)
2753-8826
DOI
10.54254/2753-8818/2/20220127
Copyright
© 2023 The Author(s)
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated