International main precious metals futures price forecasting based on decomposition-combinatorial time series model

IF 3.9 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance Pub Date : 2025-09-23 DOI:10.1016/j.najef.2025.102541

Zihan Zhang , Xiaojuan Dong , Haigang An , Hai Qi , Sufang An , Zhiliang Dong

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引用次数: 0

Abstract

In the complex and volatile macroeconomic environment, precious metals play an important role in investment risk management because of their value preservation, value-added, and hedging functions. If investors can effectively predict price fluctuations in the precious metals market and thus optimize their investment portfolio strategies in time, they may be able to avoid market risks. In this paper, the futures prices of three international precious metals on the New York Mercantile Exchange of the Wind Database from 2014 to 2024 are taken as examples. First of all, the time-varying characteristics of non-pervasive, non-Gaussian, aging and delay are obtained for precious metals. Then the trend term, seasonal term, and residual term of the price series are modeled with the Autoregressive Integrated Moving Average (ARIMA) model, the Exponen Tial Smoothing (ETS) model, and the Long-Short Term Memory (LSTM) model, respectively, and the results are summarized to form a forecast of the futures prices of precious metals for the next 100 days. The results show that the error of the combination model for the three precious metal price predictions is less than 0.03, and the model fit is more than 0.98, indicating that the decomposition-combination model is suitable for predicting the precious metal futures prices. According to the results of the study, gold and silver have investment value in a short period, while the investment value of platinum is not obvious. Corresponding investment advice for investors is also given.

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基于分解-组合时间序列模型的国际主要贵金属期货价格预测

在复杂多变的宏观经济环境下，贵金属因其保值增值和套期保值功能，在投资风险管理中发挥着重要作用。如果投资者能够有效预测贵金属市场的价格波动，从而及时优化投资组合策略，就有可能规避市场风险。本文以纽约商品交易所Wind数据库2014 - 2024年三种国际贵金属期货价格为例。首先，得到了贵金属的非普适、非高斯、时效和延迟等时变特性。然后分别采用自回归综合移动平均（ARIMA）模型、指数平滑（ETS）模型和长短期记忆（LSTM）模型对价格序列的趋势期、季节期和剩余期进行建模，并对结果进行汇总，形成未来100天贵金属期货价格的预测。结果表明，组合模型对三种贵金属价格预测的误差小于0.03，模型拟合大于0.98，表明分解组合模型适用于贵金属期货价格的预测。研究结果表明，黄金和白银在短期内具有投资价值，而铂金的投资价值不明显。并对投资者提出了相应的投资建议。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

North American Journal of Economics and Finance Multiple-

CiteScore

7.30

自引率

8.30%

发文量

168

期刊介绍： The focus of the North-American Journal of Economics and Finance is on the economics of integration of goods, services, financial markets, at both regional and global levels with the role of economic policy in that process playing an important role. Both theoretical and empirical papers are welcome. Empirical and policy-related papers that rely on data and the experiences of countries outside North America are also welcome. Papers should offer concrete lessons about the ongoing process of globalization, or policy implications about how governments, domestic or international institutions, can improve the coordination of their activities. Empirical analysis should be capable of replication. Authors of accepted papers will be encouraged to supply data and computer programs.