Forecasting Monthly Prices of Gold Using Articial Neural Network

摘要

This study successfully fitted an artificial neural network to a series on gold prices.The data used was monthly gold prices in US dollars and cents per troy ounce fromOctober 2004 to February 2020. Of the 17 suggested Artificial Neural Networkstructures, the one with 2, 6 and 1 neurons in the input, hidden and output layers(ANN (2-6-1)) was adjudged the best because it had the least error, Mean SquareError (MSE) and Mean Absolute Error (MAE). The adequacy of the selected modelwas further confirmed by graphical examination of the actual values of gold pricesand the ones predicted by the model as well as graphical residual analysis.Consequently, forecasts were made using the chosen network. The forecasts suggesta decline in gold prices in the coming months.