DOI: 10.51354/mjen.1742267 ISSN: 1694-7398

Prediction of gold price fluctuations with artificial neural networks: a comprehensive approach

Ayşe Eldem, Gülistan Ay Gülşen
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Gold is an important investment instrument of choice around the world. At the same time, its value and growth potential are of great interest. The appeal of this precious metal lies in its intrinsic value and potential for lucrative growth over time, making it a subject of intense interest and analysis among investors and economists alike. One of the key determinants of economic and social dynamics is the volatility of exchange rates and the gold market. Therefore, understanding and correctly interpreting the fluctuations of exchange rates and the gold market is of great importance for both individual investors and corporate firms. In this study, the factors affecting gold prices were investigated and the correlation between the values found and gold prices was revealed, and it was aimed to predict the change in gold price in the future with Artificial Neural Networks (ANN). The data set used in the study consists of data between January 2, 2020, and March 15, 2024. Since the markets were closed on holidays and weekends, these dates were separated and a total of 1005 days of data were used. The developed model was created and tested with different layers and neurons using MATLAB Neural Net Fitting. Results were evaluated using Coefficient of Determination (R²), Mean Squared Error (MSE) and Mean Absolute Error (MAE). The best success rate was obtained by using Levenberg-Marquardt algorithm, hyperbolic tangent sigmoid activation function in hidden layers and “purelin” linear activation function in the output layer, 4 layers and 3 neurons and 94.06% success rate was observed.

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