Gold Price Forecast: A Summary of the Integration of Economic Factors and Calculation Methods

Bowen Xie

2025

Abstract

As an essential safe-haven asset and investment tool in the global financial markets, the price movement of gold has been widely watched. The price of gold is affected by various economic factors, making its prediction challenging. In recent years, with the development of machine learning and deep learning technology, scholars have begun combining traditional econometric models with advanced computational models for gold price prediction to improve prediction accuracy and provide a reference for investment decisions. This paper synthesizes the research in gold price forecasting from the perspective of economics and computational methods. Based on the background of the gold market and the factors affecting the price, it compares the progress of the application of traditional time series models and machine learning models, discusses the performance, advantages, and disadvantages of the different models, and finally puts forward the challenges faced by the current research and the direction of future development. Several studies have shown that machine learning models incorporating economic factors have yielded promising gold price prediction results. This can better capture the nonlinear fluctuation characteristics of gold prices and provide valuable references for the investment market.

Paper Citation

in Harvard Style

Xie B. (2025). Gold Price Forecast: A Summary of the Integration of Economic Factors and Calculation Methods. In Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE; ISBN 978-989-758-765-8, SciTePress, pages 360-365. DOI: 10.5220/0013697400004670

in Bibtex Style

@conference{icdse25,
author={Bowen Xie},
title={Gold Price Forecast: A Summary of the Integration of Economic Factors and Calculation Methods},
booktitle={Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE},
year={2025},
pages={360-365},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013697400004670},
isbn={978-989-758-765-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE
TI - Gold Price Forecast: A Summary of the Integration of Economic Factors and Calculation Methods
SN - 978-989-758-765-8
AU - Xie B.
PY - 2025
SP - 360
EP - 365
DO - 10.5220/0013697400004670
PB - SciTePress