This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand�s SET50\nindex trend.ANNis a widely accepted machine learning method that uses past data to predict future trend,while GA is an algorithm\nthat can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient\nfeature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4\ninput variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction.\nThis import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that\nGA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were\nused to evaluate this hybrid intelligence prediction accuracy, and the hybrid�s prediction results were found to be more accurate\nthan those made by a method using only one input variable for one fixed length of past time span.
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