Abstract: “Stock market prediction (SMP) plays an important role in the modern era for any economy which is on the development phase. Genetic Algorithm (GA) is an evolutionary algorithm that is useful for solving problems which are too complex in nature. This paper surveys different GA models that have been experimented in stock market prediction with special enhancement techniques used with them to improve the prediction accuracy. The classification is made in terms of GA with two layer, multilayer, neural network variants and modified evolutionary algorithms. Through the surveyed paper it is shown that the performance of GA excels when integrated with other machine learning algorithms.”

Keywords: classification, enhancement technique, genetic algorithm, prediction accuracy