An Optimization of Moving Average Stock Price in Tehran Stock Exchange: Meta-heuristic approach Adaptive Improved Genetic Algorithm

Subject Areas : Journal of Investment Knowledge

Mahboobeh Asghartabar ledari ¹ , Ahmad Jafari Samimi ²

1 - Master Of Science In Rahedanesh Institute Of Higher Education (Corresponding Author)
2 - Professor Of Economics-Faculty Of Economics-Mazandaran University-Babolsar-Instructor Of Rahedanesh Institute Of Higher Education

Received: 2017-02-13 Accepted : 2017-04-05 Published : 2018-03-21

Keywords: Prediction of Stock Price – Op, Moving Average – Tehran Stock , Adaptive Improved Genetic Algo,

Abstract :

Predict the stock price is an important topic in financial markets. Is commonly use of technical tools in this area and one of them most functional, are moving averages. The use of two moving averages, the most common method to predict trends, which is in need of two periods. The optimal lengths for both short-term and long-term period for each stock, according to a recent trend, they are different. Find the optimal lengths with traditional methods of costly and often do not reach the global optimal answer. The perfect solution are using of smart tools such as genetic algorithms. Genetic algorithm have been used in this study, is Adaptive Improved Genetic Algorithm that much faster finds a global optimal answer. In this study, data's of the selected companies in diverse industries in Tehran Stock Exchange from April 2011 to March 2016 have been evaluated. The results show, when the algorithm reaches the optimal time period, which its parameters are correctly set.  

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