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Title |
An Intelligent Gold Price Prediction Based on Automated Machine and k-fold Cross Validation Learning |
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Author |
Yakubu S. Baguda and Hani Meateg Al-Jahdali |
| Citation |
Vol. 21 No. 4 pp. 65-74 |
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Abstract |
The rapid change in gold price is an issue of concern in the global economy and financial markets. Gold has been used as a means for trading and transaction around the world for long period of time and it plays an integral role in monetary, business, commercial and financial activities. More importantly, it is used as economic measure for the global economy and will continue to play an important economic vital role - both locally and globally. There has been an explosive growth in demand for efficient and effective scheme to predict gold price due its volatility and fluctuation. Hence, there is need for the development of gold price prediction scheme to assist and support investors, marketers, and financial institutions in making effective economic and monetary decisions. This paper primarily proposed an intelligent based system for predicting and characterizing the gold market trend. The simulation result shows that the proposed intelligent gold price scheme has been able to predict the gold price with high accuracy and precision, and ultimately it has significantly reduced the prediction error when compared to baseline neural network (NN). |
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Keywords |
Gold price, automated machine learning, prediction, neural network, cross validation |
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