Forecasting Silver Prices Using the Long Short-Term Memory (LSTM) Method

Silver is a versatile metal with numerous applications in human life, including industrial materials, ornaments, and investment assets. It serves as an alternative investment option due to its lower price compared to gold and its potential for value appreciation under specific market conditions. Historically stable, silver prices experienced a decline following the COVID-19 pandemic. Consequently, this study aims to forecast silver price trends to determine whether they will recover and stabilize. The forecasting is conducted using the Long Short-Term Memory (LSTM) method for a three-month period, from January 2023 to March 2023. The model’s performance is evaluated using the Mean Absolute Percentage Error (MAPE), with the best-obtained MAPE value being 0.0547. The forecasting results indicate that silver prices will experience a brief decline before rebounding.

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Publication Details

Journal
International Journal of Advanced Multidisciplinary Research and Studies
Published
2025-03-21
DOI
https://doi.org/10.62225/2583049x.2025.5.2.3909
Citations
1
Primary Topic
Stock Market Forecasting Methods
Type
article
Field-Weighted Citation Impact
2.11
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article

Forecasting Silver Prices Using the Long Short-Term Memory (LSTM) Method

Dian Kurniasari, Widiarti, Sam Kenny, Warsono Warsono
1 citations
International Journal of Advanced Multidisciplinary Research and Studies
Stock Market Forecasting Methods
2.11
article

Forecasting Silver Prices Using the Long Short-Term Memory (LSTM) Method

Dian Kurniasari, Widiarti, Sam Kenny, Warsono Warsono
article en
1 citations

Abstract

Silver is a versatile metal with numerous applications in human life, including industrial materials, ornaments, and investment assets. It serves as an alternative investment option due to its lower price compared to gold and its potential for value appreciation under specific market conditions. Historically stable, silver prices experienced a decline following the COVID-19 pandemic. Consequently, this study aims to forecast silver price trends to determine whether they will recover and stabilize. The forecasting is conducted using the Long Short-Term Memory (LSTM) method for a three-month period, from January 2023 to March 2023. The model’s performance is evaluated using the Mean Absolute Percentage Error (MAPE), with the best-obtained MAPE value being 0.0547. The forecasting results indicate that silver prices will experience a brief decline before rebounding.

International Journal of Advanced Multidisciplinary Research and StudiesVol. 5(2)
Openalex Percentile: Top 15%
Stock Market Forecasting Methods
2.11
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Forecasting Silver Prices Using the Long Short-Term Memory (LSTM) Method — Dian Kurniasari, Widiarti, et al. · International Journal of Advanced Multidisciplinary Research and Studies (2025) | TGRS Research Map | TGRS