Adaptación de una red neuronal para la negociación en el mercado de divisas

Abstract

In this thesis, several machine learning techniques are explored and applied to the investment decision problem. Some indicators of technical analysis are used as inputs of a neural network which is trained to determine, with each input vector, a buy, sell or hold signal. Likewise, the structure of the network is optimized by applying a genetic algorithm, in order to determine its adequate depth. With this work, some bases are established to perform different empirical studies that improve and deepen the analyzed topics.