Abstract

Estimating Stock Returns Using Artificial Neural Networks: An Experimental Design With An Evidence From Iraq Stock Exchange

Mohammed H Adnan, Mustafa Muneer Isma’eel

Volume: 11 Issue: 2 2021

Abstract:

The research aims to estimate stock returns using artificial neural networks and to test the performance of the Error Back Propagation network, for its effectiveness and accuracy in predicting the returns of stocks and their potential in the field of financial markets and to rationalize investor decisions. A sample of companies listed on the Iraq Stock Exchange was selected with (38) stock for a time series spanning (120) months for the years (2010_2019). The research found that there is a weakness in the network of Error Back Propagation training and the identification of data patterns of stock returns as individual inputs feeding the network due to the high fluctuation in the rates of returns leads to variation in proportions and in different directions, negatively and positively.

DOI: http://doi.org/10.37648/ijrssh.v11i02.017

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