Company financial strategic analysis using neural classifiers

One of the most important problems that firm management has to solve in strategic analyses of companies is how balance-sheet items are correlated with a success of a firm. This paper describes a neural classifier whose main task is to describe the success of a firm´s capabilities in terms of balance-sheet items. We used balance-sheet items from the last three years of the most important Italian clothing-textile companies. A backpropagation algorithm is used to perform convergence of learning and test cases. To define what kind of financial profile a firm needs in order to be competitive we apply the classification system built to simulate cases for which targets are not noted a priori. This methodology gives us important information, which is impossible to acquire with alternative methodology, about the behaviour a firm has to adopt in order to increase its competitiveness