Title of article :
Predicting the Effective Factors on Concurrency of Stock Price Considering Corporative Governing Based on Neural Network
Author/Authors :
Ataeizadeh ، Reza Young Researchers and Elite Club - Islamic Azad University, Ardabil Branch , Abdollahi ، Fereshteh Department of Accounting - Islamic Azad University, South Tehran Branch , Mohagheghi ، Hushang Department of Management - Islamic Azad University, Semnan Branch
Abstract :
The aim of this research is predicting the effective factors on concurrency of stock price considering corporative governing based on neural network. This study is based on Neural Network. The data of 93 financial companies listed on Tehran Stock Exchange during the period of 6 years (2009-2015) have been studied. The sample is divided into two categories of testing and training. The results of analysis suggest that since the amount of error in testing sample is equal to training sample, thus model fitness is acceptable; Also, the results of table 7 represent that financial leverage, company size, growth opportunity, standard deviation of unlevered cash flow, standard deviation of daily yield, and controlling shareholders is effective on the concurrency of stock price.
Keywords :
Concurrency of stock price , Controlling Shareholders , Neural Network
Journal title :
International Journal of Management,Accounting and Economics(IJMAE)
Journal title :
International Journal of Management,Accounting and Economics(IJMAE)
