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March 6, 2026SHILAP Revista de lepidopterología1 citationsOpen Access

Investment Instruments: The Power of Neural Networks in Predicting Gold Price Trends

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JHJakub HorákMVMarek VochоzkaDKDominik Kaisler

Key Points

  • The research aims to evaluate gold's market position and assess the forecasting capability of neural networks on its price trends.
  • Conducted time series analysis using historical gold price data from 2000 to March 2023.
  • Examined the influence of political, economic, technological, and social factors on gold prices.
  • Utilized artificial neural networks to predict gold price movements.
  • Identified key factors affecting historical gold prices, including political and economic aspects.
  • Found that neural networks accurately predict gold price trends, mirroring genuine price development curves.
  • Concluded that gold serves as a viable financial resource and investment opportunity.

Abstract

Precious metals, and especially gold, have been inextricably linked to the history of mankind since time immemorial. In modern times, gold has become a key factor in international trade and the global economy. Therefore, for example, oil price fluctuations can be a predictor of gold price movements. Today, gold is seen as an independent financial asset that has become a popular tool for portfolio diversification, as well as a hedge against inflation. For this reason, this topic is considered to be very important and topical worldwide, attracting the attention of a wide range of people, both from the ranks of experts and the lay public. The article’s objectives are to determine the position of gold in the commodity market, measure and compare the metal’s historical price development from 2000 to March 2023, and, last but not least, assess how well artificial neural networks can forecast the movement of gold’s market price. Evaluating whether gold is a good financial resource multiplier or custodian is one of the partial goals. In order to achieve this goal, time series analysis will be performed using artificial neural networks. It is feasible to track how accurately artificial neural networks can forecast changes in market prices by using this technique. The results show that the most common elements influencing the historical development of the price of gold were political, economic, technological, and social aspects. Additionally, it was shown that artificial neural networks are capable of accurately predicting the course of the price of gold and, thus, mimicking the genuine price development curve. Based on the obtained results, future studies might be carried out to compare a more extensive portfolio of commodities in order to build on this work. The contribution is beneficial both on a theoretical and practical level. It can serve investors, analysts, economists, and other authors dealing with this issue.

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Cite This Study

Horák et al. (2024) studied this question.

synapsesocial.com/papers/69aa6eb1531e4c4a9ff58e11https://doi.org/10.23762/fso_vol12_no1_4
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