企業危機預警模式之研究－DEA-DA、邏輯斯迴歸與類神經網路之應用

A study on Prediction Models of Financial Distress-A comparison of DEA-DA、Neural Network and Logistic Regression

林淑萍(Shu-Ping Lin) ； 黃劭彥(Shiao-Yan Hwang) ； 蔡昆霖(Kuen-Lin Tsai)

《會計與公司治理》 4卷1期 (2007/06) Pp. 35-56

https://doi.org/10.30139/JACG.200706.0002

摘要

為有效建立企業之危機預警模式，本研究利用過去相關文獻常用之財務指標（包含應收帳款週轉率、流動比率、每股盈餘與負債比率），以DEA-DA、邏輯斯迴歸與類神經網路等三種不同之研究方法，來比較其判別正確率與預測正確率。研究結果發現三種方法所建立的預測模式，其判別正確率與預測正確率均達80%以上，其中邏輯斯迴歸判別之敏感度僅為33.3%，但精確度為100%，而DEA-DA及類神經網路之敏感度均達60%以上，精確度均超過85%。

關鍵字

財務危機 ； 預警模式 ； DEA-DA ； 邏輯斯迴歸 ； 類神經網路

並列摘要

In this paper, we first survey the relative literatures to find the financial indicators. And then we use the methods of DEA-DA、neural network and logistic regression by the financial indicators to establish the prediction models of financial distress. In the main results, we discover that the hit rates of these three models are at least 80%. Furthermore, the sensitivity is 33.3% and the specificity is 100% for the logistic regression model. The sensitivity is more than 60% and the specificity are more than 60% and the specificity are more than 85% for the DEA-DA and neural network models.

並列關鍵字

Financial distress ； Prediction model ； DEA-DA ； Logistic regression ； Neural network

參考文獻

Altman, E. I.(1968).Financial ratios: Discriminant analysis and the prediction of corporate bankruptcy.Journal of Finance.23(4),589-609.

Altman, E. I.,G. V. Marco,F. Varetto.(1994).Corporate distress diagnosis: Comparisons using linear discriminate analysis and neural networks.Journal of Banking and Finance.18(3),505-529.

Altman, E. I.,R. Haldeman,P. Narayanan.(1977).ZETATM analysis: A new model to identify bankruptcy risk of corporations.Journal of Banking and Finance.1(1),29-54.

Beaver, W. H.(1966).Financial ratios as predictors of failure.Journal of Accounting Research.4(3),71-111.

Blum, M.(1974).Failing company discriminant analysis.Journal of Accounting Research.12(1),1-25.