- Autor
- Horak Jakub (The Institute of Technology and Business, Ceske Budejovice, Czech Republic), Vochozka Marek (DTI University, Slovak Republic), Kaisler Dominik (The Institute of Technology and Business, Ceske Budejovice, Czech Republic)
- Tytuł
- Investment Instruments: The Power of Neural Networks in Predicting Gold Price Trends
- Źródło
- Forum Scientiae Oeconomia, 2024, vol. 12, no. 1, s. 72-95, rys., tab., bibliogr. 34 poz.
- Słowa kluczowe
- Sztuczna inteligencja, Inwestowanie, Handel międzynarodowy
Artificial intelligence, Investing, International trade - Uwagi
- summ.
- Abstrakt
- Precious metals, and especially gold, have been inextricably linked to the history of man-kind since time immemorial. In modern times, gold has become a key factor in interna-tional trade and the global economy. erefore, 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 world-wide, attracting the attention of a wide range of people, both from the ranks of experts and the lay public. e article's objectives are to determine the position of gold in thecommodity 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 goodfinancial 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. e 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. e contribution is beneficial both on a theoretical and practical level. It can serve inves-tors, analysts, economists, and other authors dealing with this issue.(original abstract)
- Pełny tekst
- Pokaż
- Bibliografia
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- Cytowane przez
- ISSN
- 2300-5947
2353-4435 - Język
- eng
- URI / DOI
- http://dx.doi.org/10.23762/FSO_VOL12_NO1_4