INVESTMENT GOLD DURING THE COVID-19 PANDEMIC WITH LINEAR REGRESSION, NONLINEAR REGRESSION AND ARIMA

As a result of the COVID-19 pandemic, many individuals have turned to low-risk investment options. Common choices include gold, stocks, deposits, and foreign currencies, with gold emerging as a particularly popular investment. This study aims to forecast gold prices using linear regression, nonlinear regression, and ARIMA models, with the most accurate model determined by the lowest Mean Absolute Percentage Error (MAPE). Gold price data was sourced from www.kitco.com. The MAPE for the Linear Regression model was 4.362, the Nonlinear Regression model 3.3428, and the Time Series (ARIMA) model 2.727. Consequently, the ARIMA model demonstrated superior accuracy in forecasting gold prices compared to the Linear and Nonlinear Regression models.

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Publication Details

Journal
Journal of Mathematics Computations and Statistics
Published
2025-03-27
DOI
https://doi.org/10.35580/jmathcos.v8i1.6832
Primary Topic
Management and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

INVESTMENT GOLD DURING THE COVID-19 PANDEMIC WITH LINEAR REGRESSION, NONLINEAR REGRESSION AND ARIMA

Yan Batara Putra Siringoringo, Erwin Erwin, M Yanti, Citra Dewi Hasibuan et al.
Journal of Mathematics Computations and Statistics
Management and Optimization Techniques
article

INVESTMENT GOLD DURING THE COVID-19 PANDEMIC WITH LINEAR REGRESSION, NONLINEAR REGRESSION AND ARIMA

Yan Batara Putra Siringoringo, Erwin Erwin, M Yanti, Citra Dewi Hasibuan, Enita Dewi Tarigan
article en

Abstract

As a result of the COVID-19 pandemic, many individuals have turned to low-risk investment options. Common choices include gold, stocks, deposits, and foreign currencies, with gold emerging as a particularly popular investment. This study aims to forecast gold prices using linear regression, nonlinear regression, and ARIMA models, with the most accurate model determined by the lowest Mean Absolute Percentage Error (MAPE). Gold price data was sourced from www.kitco.com. The MAPE for the Linear Regression model was 4.362, the Nonlinear Regression model 3.3428, and the Time Series (ARIMA) model 2.727. Consequently, the ARIMA model demonstrated superior accuracy in forecasting gold prices compared to the Linear and Nonlinear Regression models.

Journal of Mathematics Computations and StatisticsVol. 8(1)
Universitas Sumatera Utara (ID)
Universitas Sumatera Utara
Openalex Percentile: Top 84%
Management and Optimization Techniques
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