
Bankruptcy prediction is more important than a changing of the stock price for investors because they will have a big loss if the investing company goes bankrupt. There are some methods using discriminant analysis, such as Altman's Z-score for the bankruptcy prediction. However, these methods have a problem that their precisions decrease when there is a big difference between the number of the bankruptcy companies and the existing companies. It is also difficult for them to predict the black-ink bankruptcy in recent years because they adopt general management indices. This paper describes a new bankruptcy prediction system available even in such cases by adopting "Cash Flows" which must be more important indices than the profit, sales and so on in the bankruptcy. First, the system selects cash flow indices by factor analysis to hundle the money changes. Second, the system makes a SOM map and predict bankruptcies by evaluating not individual company indices but interrelationships between companies indices by SOM. Third, prediction errors and their accuracies are discussed. Finally, we compare results of our method with those of the discriminant analysis including Altman's Z-score and show the usefulness of our method.
キャッシュ・フロー, Self-organizing Maps, Self-organizing maps, 判別分析, 因子分析, Cash flow, 倒産予測, Bankruptcy prediction, 自己組織化マップ, Factor analysis, Discriminant analysis
キャッシュ・フロー, Self-organizing Maps, Self-organizing maps, 判別分析, 因子分析, Cash flow, 倒産予測, Bankruptcy prediction, 自己組織化マップ, Factor analysis, Discriminant analysis
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