Research on the Prediction of the Global Price of Gold

Zining Chen

2025

Abstract

Gold, as a safe-haven and value-preserving asset, has been brought to worldwide attention. However, its price is influenced by numerous factors, making it difficult to predict and causing many investors to hesitate about whether to invest. The Autoregressive Integrated Moving Average (ARIMA) model, a time series model, has gained recognition and widespread adoption due to its accuracy. In this paper, the ARIMA model is used to predict gold prices from Feb 22 to Mar 23. The findings indicate that the predicted values also suggest further increases. The residual test confirms that the residuals of the ARIMA model's predictions exhibit pure randomness, thereby validating the model's accuracy. This study confirms the effectiveness of the ARIMA model in short-term gold price forecasting, yet its limitation lies in the difficulty of predicting the multiple factors influencing gold prices. Future research may consider incorporating additional exogenous variables and nonlinear models to enhance long-term predictive performance.

Paper Citation

in Harvard Style

Chen Z. (2025). Research on the Prediction of the Global Price of Gold. In Proceedings of the 2nd International Conference on Innovations in Applied Mathematics, Physics, and Astronomy - Volume 1: IAMPA; ISBN 978-989-758-774-0, SciTePress, pages 379-383. DOI: 10.5220/0013826300004708

in Bibtex Style

@conference{iampa25,
author={Zining Chen},
title={Research on the Prediction of the Global Price of Gold},
booktitle={Proceedings of the 2nd International Conference on Innovations in Applied Mathematics, Physics, and Astronomy - Volume 1: IAMPA},
year={2025},
pages={379-383},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013826300004708},
isbn={978-989-758-774-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Innovations in Applied Mathematics, Physics, and Astronomy - Volume 1: IAMPA
TI - Research on the Prediction of the Global Price of Gold
SN - 978-989-758-774-0
AU - Chen Z.
PY - 2025
SP - 379
EP - 383
DO - 10.5220/0013826300004708
PB - SciTePress