A Forecast Analysis of the Gold Stock Price Using ARIMA Model

Authors

  • Wenbo Lyu Saxo Fintech Business School, University of Sanya, Sanya, 572000, China.
  • Yi Yang Saxo Fintech Business School, University of Sanya, Sanya, 572000, China.
  • Zhiyuan Li Saxo Fintech Business School, University of Sanya, Sanya, 572000, China.
  • Jiale Niu Saxo Fintech Business School, University of Sanya, Sanya, 572000, China.
  • Yuhan Li Saxo Fintech Business School, University of Sanya, Sanya, 572000, China.

DOI:

https://doi.org/10.9734/bpi/mono/978-93-48388-89-6/CH37

Keywords:

Gold stock prices, ARIMA model, time series analysis, prediction accuracy

Abstract

This paper proposes a time series method using the ARIMA model to forecast gold-stock prices. It involves data preprocessing, model building, tuning, prediction, and result analysis to guide investment decisions. The ARIMA model, with its selection and validation processes, demonstrates strong performance in predicting gold prices over four months. Comprehensive analysis considers macroeconomic, geopolitical, and market fundamentals influencing gold prices. The research emphasizes the significance of understanding and modeling gold's behavior for preserving wealth in a volatile financial landscape.

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Published

2024-11-20

How to Cite

Wenbo Lyu, Yi Yang, Zhiyuan Li, Jiale Niu, & Yuhan Li. (2024). A Forecast Analysis of the Gold Stock Price Using ARIMA Model. Theoretical Key Issues and Practical Development Trends of China’s Digital Economy, 792–817. https://doi.org/10.9734/bpi/mono/978-93-48388-89-6/CH37

Issue

Theoretical Key Issues and Practical Development Trends of China's Digital Economy

Section

Contents