in financial distress studies selection of variable is commonly basedon the success of variables in variable sets employed in earlierbankruptcy studies, suggestions in the literature or an accompanyingdata reduction in a large set of variables. if seemingly different variablesets exhibit a strong relationship then heterogeneous variable setscapture common information. canonical correlation anal...

the development of the cyprus stock exchange together with the increasing trend of investors’ presence in financing activities has led to the importance of this market. in such circumstances, the first step towards a sustainable development of the exchange is to support the investors. risk of bankruptcy for the investee is a major challenge that an inexperienced stock investor encounters. in th...

Bankruptcy is one of the most important issues in Financial Management and investment. Numerous studies on Bankruptcy Prediction have been carried out considering Quantitative factors and they applied different techniques on it to predict Bankruptcy, while only fewer studies have proposed and considered Qualitative factors for prediction of Bankruptcy and even then failure of bankruptcy persist...

Nowadays, prediction of corporate bankruptcy is one of the most important issues which have received great attentions among academia and practitioners. Although several studies have been accomplished in the field of bankruptcy prediction, less attention has been devoted for proposing a systematic approach based on fuzzy neural networks.  The present study proposes fuzzy neural networks to predi...

The development of the Cyprus Stock Exchange together with the increasing trend of investors’ presence in financing activities has led to the importance of this market. In such circumstances, the first step towards a sustainable development of the Exchange is to support the investors. Risk of bankruptcy for the investee is a major challenge that an inexperienced stock investor encounters. In th...

the main purpose of this paper is prediction of tse corporate financial bankruptcy using artificial neural networks. the mean values of key ratios reported in past bankruptcy studies were selected for neural network inputs (working capital to total assets, net income to total assets, total debt to total assets, current assets to current liabilities, quick assets to current liabilities). the neu...

With the recent financial crisis and European debt crisis, corporate bankruptcy prediction has become an increasingly important issue for financial institutions. Many statistical and intelligent methods have been proposed, however, there is no overall best method has been used in predicting corporate bankruptcy. Recent studies suggest ensemble learning methods may have potential applicability i...

Because of the recent surge in U.S. personal defaults, Congress is currently debating bankruptcy reform legislation requiring a means test for Chapter 7 filers. This paper explores the effects of such a reform in a model where, in contrast to previous work, bankruptcy options and production are explicitly taken into account. Our findings indicate that means testing would not improve upon curren...

Data envelopment analysis (DEA) is an effective tool for supporting decision-makers to assess bankruptcy, uncertainty concepts including intervals, and game theory. The bankruptcy problem with the qualitative parameters is an economic problem under uncertainty. Accordingly, we combine the concepts of the DEA game theory and uncertain models as interval linear programming (ILP), which can be app...