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Forthcoming Articles
Volume 3, Number 2 / June 1999 , Pages 71-145
Multinational Finance Journal, 1999, vol. 3, no. 2, pp. 71-101 | https://doi.org/10.17578/3-2-1
Michael Doumpos , Technical University of Crete, Greece    Corresponding Author
Constantin Zopounidis , Technical University of Crete, Greece

Abstract:
Financial distress prediction is an essential issue in finance. Especially in emerging economies, predicting the future financial situation of individual corporate entities is even more significant, bearing in mind the general economic turmoil that can be caused by business failures. The research on developing quantitative financial distress prediction models has been focused on building discriminant models distinguishing healthy firms from financially distressed ones. Following this discrimination approach, this paper explores the applicability of a new non–parametric multicriteria decision aid discrimination method, called M.H.DIS, to predict financial distress using data concerning the case of Greece. A comparison with discriminant and logit analysis is performed using both a basic and a holdout sample. The results show that M.H.DIS can be considered as a new alternative tool for financial distress prediction. Its performance is superior to discriminant analysis and comparable to logit analysis.

Keywords : discrimination; financial distress; mathematical programming; multi-criteria decision aid
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Multinational Finance Journal, 1999, vol. 3, no. 2, pp. 103-125 | https://doi.org/10.17578/3-2-2
Sunti Tirapat , Chulalongkorn University, Thailand    Corresponding Author
Aekkachai Nittayagasetwat , National Institute of Development Administration, Thailand

Abstract:
The emergence of the economic crisis in Thailand in 1997 is an interesting case for academic studies. Internationally, it had a contagion effect, spreading to countries in Asia and in other regions. Domestically, it caused a great many industrial and corporate bankruptcies. The Thai economy had been relatively stable since 1984. The recent development in 1997, however, produced a sudden economic slump resulting in closures of many Thai corporations. Using a logit regression, this study develops a macro-related micro-crisis investigation model. The significance of the model is in its ability to bridge a firm's sensitivity to macroeconomic conditions and its financial characteristics in order to explore a firm's financial distress. The findings indicate that macroeconomic conditions are critical indicators of potential financial crisis for a firm. The article shows that the higher a firm's sensitivity to inflation, the higher the firm's exposure to financial distress.

Keywords : bankruptcy; financial distress; prediction model; and Thailand crisis
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Multinational Finance Journal, 1999, vol. 3, no. 2, pp. 127-145 | https://doi.org/10.17578/3-2-3
Obeua S. Persons , Rider University, U.S.A.    Corresponding Author

Abstract:
This article combines qualitative and quantitative information from financial statements and auditors' reports with logistic models to differentiate failed from surviving finance companies in Thailand. Failed companies are those that were forced to suspend their operations in mid-1997. The results indicate that auditors' reports from the 1996 financial statements did not differentiate failed from surviving finance companies. On the other hand, the logistic regression models indicate that failed finance companies had lower profitability, lower foreign borrowing possibly due to their poorer credit rating, lower management quality, and smaller size. These models have relatively high predictive ability for failed finance companies and low expected costs of misclassification

Keywords : CAMEL; emerging economies; financial failure; logistic model; Thailand
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