Predicting the Direction of Stock Market Prices Using Random Forest

Subject Areas : Financial engineering

elham gholamian ¹ , sayyed mohammad reza davoodi ²

1 - Masters Student in Industrial Engineering- Economic and Social Systems Engineering, Dehaghan Branch, Islamic Azad University, Dehaghan, Iran,
2 - Assistant Professor. Department of Management ,Dehaghan Branch, Islamic Azad University, Dehaghan, Iran

Received: 2017-10-24 Accepted : 2017-12-11 Published : 2018-06-22

Keywords: Entropy, Logistic regression, technical indicators, Random forest algorithm, stock price prediction,

Abstract :

Stock market activists are the acquiring and using methods to predict future stock prices, increasing their capital gains. Therefore, it seems necessary that appropriate, correct, and scientific principles are used to determine the future price of the stock of investor stock options.stock price prediction is an important part of investment, and in most cases it is the field of research for researchers, because it ultimately leads to the choice of appropriate investment. Different methods have now been developed to achieve this goal. Have been introduced that are often statistical methods and artificial intelligence. In this research, using a randomized approach approach that is among artificial intelligence classification methods, along with technical indicators that include: power index Relative Price, Stochastic, Equilibrium Balance, Williams R%, Daily Returns, and Mac.d Series Markets, are looking for stock price trends. This model is compared with logistic regression method and completely randomized method (dice throw). The results of the research on daily data of Tehran Stock Exchange Index from 1393 to 1395 indicate that the accuracy of the proposed method in estimating market trend is 64%, which is more than two methods of logistic regressionand completely randomized method of accuracy Has a higher rate.