Volume 50, Issue 3 (2025)
Economic Factors Affecting Gold Prices Pre-COVID-19, during COVID-19 Period and Next-Normal for Gold Price Forecasting Using ARIMA Model
(Pages 358-373)
Author(s)
Suphattana Tachochalalai1, Somkid Yakean2,*, Konnut Pugatekaew2, Chanchai Pommi2, Piyaphong Supanyo2 and Suriya Suwannathipyachot2
1Faculty of Business Administration, Rajamangala University of Technology Krungthep, Bangkok, 10120, Thailand; 2School of Business and Communication Arts, University of Phayao, 56000, Thailand
Abstract:
This study investigates the impact of macroeconomic variables on gold prices in Thailand and develops an ARIMA forecasting model across three distinct phases: pre-the COVID 19 period (January 2011 to March 2020), the COVID-19 period (April 2020 to October 2021), and the next-normal period (November 2021 to December 2024). Multiple regression analysis is applied to examine the relationships between Thai gold prices and five key macroeconomic variables: SET Index, USD/THB exchange rates, crude oil prices, Consumer Price Index, and gold price volatility. Additionally, an ARIMA model is developed for gold price forecasting.
Based on experimental results, this study demonstrates that the relationships between these variables shift across different timeframes. In the pre-the COVID-19 period, SET Index and ex change rates served as strong gold price predictors. The COVID-19 period disrupted conventional associations between macroeconomic variables and gold prices, whereas the next-normal period restored the importance of these macroeconomic variables, indicating market recovery. The ARIMA model constructed effectively predicts gold prices with reliable precision. Results validate gold’s dual function as both an inflation protection mechanism and a crisis-period in vestment, with correlations changing during economic instability. The SET Index maintained consistent inverse relationships with gold prices, reinforcing the opposing dynamics between equity markets and precious metal investment. These findings offer crucial insights for investment portfolio management and government economic policy formulation. The ARIMA frame work provides traders with effective instruments for short-term price prediction, improving risk assessment capabilities during market volatility and supporting strategic decision-making during periods of economic uncertainty.
Keywords:
Gold Price, ARIMA, Forecasting, Macroeconomics, COVID-19.
Cite this paper:
Suphattana Tachochalalai, Somkid Yakean, Konnut Pugatekaew, Chanchai Pommi, Piyaphong Supanyo and Suriya Suwannathipyachot, Economic Factors Affecting Gold Prices Pre-COVID-19, during COVID-19 Period and Next-Normal for Gold Price Forecasting Using ARIMA Model, The Journal of Social, Political and Economic Studies. Volume 50, Issue 3, Year 2025 | PP. 358-373. https://thejspes.com/vol50-a29
© 2025 The Author(s). Published by 'The Journal of Social, Political and Economic Studies'.
This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial 3.0 License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The Journal of Social, Political and Economic Studies supports the free dissemination of academic knowledge under these terms.