An application of Altman-levalle and legault-Veronneau models for prediction of continuity and bankruptcy in accepted companies in TSE (Tehran Stock Exchange)

In recent decades, the dominant conditions in economy such as Increasing speed of change in production technologies, growth and expension of markets, extensive range of exchange among industries,focusing on custmore-oriented approaches and change in competition basics and product variations form one hand, and concern about bankruptcy reports in economy of the world , on the other hand leads to alteration of attitudes of economists and planners in terms of resourse allocation with the aim of reducing bankruptcy –related investmsnt risk. therefore,indentification and prediction the scope of business in relation to the interests of wild rang of stakeholders seems something to be dsirabe and critical.
Statistical models, Artificially Intelligent Expert System models and Theoretic models approaches are used by researchers to predict the business scppe, focusing on symptom of bankruprcy in Statistical models and Artificially Intelligent Expert System models but Theoretic models merily concern about the causes leading to bankruptcy. Each model has some advantage and disadvantage .although the methods differ in the models, there is no difference interms of effect and outcome.
The results show that the both befitted models are able to predict the bankruptcy of accepted companies in the stock exchange,general accuracy levels of prediction for modified version of Altman-Levalle model 91.85% and 84.7% for one year and two years before bankruptcy events respectively and the same levels for modified version of Legault-Veronneau model are 88.8% and 86.7% for one year and tow years before bankruptcy events respectively. Thus, the firt and the second hypothesis are confirmed but for the third, it is concluded that there is no differnens between the two modles in terms o f their application, that is, the third Hypothesis is rejected.