Artificial neural networks applied to the pbkp_rediction of the gold price

Abstract:

Gold price pbkp_rediction using an artificial neural network model (ANN) is proposed in this work. The objective of the model is to pbkp_redict the daily closing prices in the London market, which are taken as reference prices for the Central Bank of Colombia. Different configurations of type feed-forward ANN are considered using the dollar index DXY, the SP500 index, the daily oil price series, and the daily gold price series, as inputs to the ANN model. A set of ANN structures are trained using the historical series of data, where one portion is used for training and the other portion is used for testing (pbkp_rediction). The results show good performance of the model both in the analyzed historical period and the pbkp_redictions, where the best structure includes the daily price series of gold, the DXY index and the SP500 index.

Año de publicación:

2016

Keywords:

• Price pbkp_rediction
• Neural networks
• financial markets
• Gold exchange market

Fuente:

scopus