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Boletín de Ciencias de la Tierra
Print version ISSN 0120-3630
Abstract
FRANCO-SEPULVEDA, GIOVANNI; VELILLA-AVILEZ, DANILO ARTURO and VELEZ-JARAMILLO, INGRID ESTEFANÍA. COAL PRICE ANALYSIS BY ARTIFICIAL NEURAL NETWORKS (ANN). Bol. cienc. tierra [online]. 2014, n.35, pp.31-36. ISSN 0120-3630. https://doi.org/10.15446/rbct.n35.39682.
This article develops the approximate analysis of the Free on Board Price (FOB) of thermal coal in Colombia for the period 2012-2020. For the estimation it was used the artificial neural networks model as a methodological foundation work. In order to understand how the price of the commodity is affected by the economic, political and social characteristics of each space-time, we review the historical behavior of the price of coal in the international scope and the geopolitical context in which these were framed, identifying a period of 32 years approximately. Likewise, an analysis of price behavior by using the DJIA index and its relation to the nominal prices of coal, and real prices deflacted to present value of 2012. Then we obtain the prediction of prices using the predictive model generated by the neural network algorithm used, ending with the approach of the conclusions obtained according to the results.
Keywords : Coal; artificial neural network; DJIA; cycle; market.