Detecting companies' financial distress by multi-attribute decision-making model

Abstract

In recent years, financial crisis events related to the public companies have obtained more and more attentions. In this paper, we proposed a novel multi-attribute decision-making model to forecast the possibility of companies' financial distress. The proposed model contains two main phases, which are attribute weight computing and financial distress detecting. Experiments conducting on 20 companies' from shanghai or shenzhen stock markets show that the proposed model performs better than other methods in most cases, and our model can effectively detect the financial distress in early stage. © 2013 Springer-Verlag.