Compare the performance of Artificial Neural Network and Logistic Regression In Discriminant Analysis Tobin's q index

Tobin index is one of the most important indices in the world of investment used as a criterion for evaluating performance of the firms to decide for the right investments. However, there are some ambiguities in the accuracy of the results based on this index that have prompted researchers to pursue estimation of this index based on the other financial indices. But Tobin index is a dynamic index and as it is based on the market price, may be changed its value at once, therefore it is not logical to be predicted using methods as multiple regression that attempt to predict precise value of depent variable. this research has reviewed methods based on the exact prediction like regression to judge about Tobin index by the other financial indices and it has recommended using discriminant analysis methods such as logistic regression and artificial nervous network. Discriminant analysis is a method to categorize a set of the observations into one of two or several determined groups, so that observations within each group can have the most similarity to each other. Therefore, this research has analyzed Tobin index discrimination using financial information of 184 accepted firms by Tehran Stock Exchange in the financial year leading to 29 of Esfand in 1393 by logistic regression and artificial nervous network and it has reported results of two techniques and has compared output of the two techniques to each other.