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

Jakub Horak; Marek Vochozka; Dominik Kaisler

doi:10.23762/FSO_VOL12_NO1_4

Published : 2024-03-31

Vol. 12 No. 1 (2024)

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

Jakub Horak

https://orcid.org/0000-0001-6364-9745

Marek Vochozka

https://orcid.org/0000-0001-9923-7814

Dominik Kaisler

https://orcid.org/0009-0006-7497-1389

DOI: https://doi.org/10.23762/FSO_VOL12_NO1_4

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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gold, prediction, artificial intelligence, commodity market, investing.

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Horak, J., Vochozka, M., & Kaisler, D. (2024). Investment Instruments: The Power of Neural Networks in Predicting Gold Price Trends. Forum Scientiae Oeconomia, 12(1), 72–95. https://doi.org/10.23762/FSO_VOL12_NO1_4

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