Prediction of Stock Returns Using Financial Ratios Based on Historical Cost, Compared with Adjusted Prices (accounting for Inflation) with Neural Network Approach

The purpose of this research is to predict stock returns and the purpose of the least squares regression and neural network approach is used. The potential financial ratios based on the historical cost and financial ratios based on Adjusted Cost predict stock returns are investigated. Independent variables and the dependent variable in this study and financial ratios and stock returns is for these purpose financial ratios for listed companies in Tehran Stock Exchange for the period 2007 to 2012 were collected. The results showed that the predicted stock returns based on financial ratios financial ratios adjusted based on the general price index and the use of neural networks better performance in comparison with the historical financial ratios and least squares regression approach in predicting stock returns has the variables are adjusted based on the general price index, variables, net profit margin, return on assets, current ratio, asset turnover ratio and fixed assets turnover ratio, respectively, are of the greatest importance and impact.