Gold Price Forecasting: A Novel Approach Based on Text Mining and Big-Data-Driven Model

Saeed Kian Poor; Shahram Fattahi; Mohsen Hajian

doi:10.2478/sbe-2024-0049

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Gold Price Forecasting: A Novel Approach Based on Text Mining and Big-Data-Driven Model

Studies in Business and Economics

Volume 19 (2024): Issue 3 (December 2024)

By: Saeed Kian Poor, Shahram Fattahi and Mohsen Hajian

Open Access

|Jan 2025

Abstract

This work uses Google Trends and online text mining to test a novel approach to gold price prediction. To explain the gold price prognosis, the convolutional neural network (CNN) also uses linguistic criteria for news items about gold. The findings of this study can be used to explain the theoretical underpinnings of information processing worldwide. According to experimental findings, big data forecasting and online data mining are more efficient than other methods. As a result, utilizing 19926 in sum news headlines acquired, the synergistic connection between news items and Google Trends is successful in accurately projecting the price of gold.

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Articles in this issue

DOI: https://doi.org/10.2478/sbe-2024-0049 | Journal eISSN: 2344-5416 | Journal ISSN: 1842-4120

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Language: English

Page range: 156 - 171

Published on: Jan 22, 2025

Published by: Lucian Blaga University of Sibiu

In partnership with: Paradigm Publishing Services

Publication frequency: 3 issues per year

Keywords:

gold price Prediction,

Trends,

Online News,

Data Mining,

CNN

Related subjects:

Business and economics,

Business management,

Management accounting, financial controlling, cost calculation, investment,

Management, organization, corporate governance,

Business development, change management, cooperation,

Entrepreneurship

© 2025 Saeed Kian Poor, Shahram Fattahi, Mohsen Hajian, published by Lucian Blaga University of Sibiu
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 19 (2024): Issue 3 (December 2024)