本研究主要探討利用Altman破產模型(Altman Bankruptcy Model)原先所定義的變數以及羅吉斯信用評等迴歸模型(Logistic Regression Credit Rating Model)衡量最近十年台灣共323家上市櫃公司的危機預警情形，衡量危機發生的前一年及前兩年的預警能力。
由於近年國際社會經濟狀況持續不景氣，時常可見大型公司乃至政府財務違約事件層出不窮，公司借款成本持續低檔導致資金浮濫，控管違約機率已成銀行重要課題，銀行本身內部設計出一套信評模型，對各種不同產業多面向評估違約機率，期能減少呆帳發生的機率進而降低損失。
Altman模型可說是危機預警模型的始祖，國內外許多研究也根據此理論基礎加以創新及改進，本文除了以原模型驗證之外，再嘗試以羅吉斯回歸建立信評模型，另外加上一個自定義的變數設計出新模型，測試危機預警的能力，最後再與銀行內建信評模型進行對照，綜合考量下發現預警正確率仍以傳統Altman破產模型最佳。型一與型二誤差在增加變數下無法有效下降。

This research’s main discussion is using Altman Bankruptcy Model and Logistic Regression Credit Rating Model to measure 323 public offering company of crisis warning case in the last ten years in Taiwan, measuring finance crisis occurred before a years and two years of warning capacity .
Due to the economic recession in recent years worldwide , many large company and government default event occurred endlessly. Company borrowing cost stayed at low point led to funds floating. Controlling default chances has become the most important subject for banks.
Banks itself has an built in assessment model on various industry to assess default chances in different faces, hoping to reduce the chances of default and reduce loss at the same time, Altman Bankruptcy model is said to be the ancestor of crisis warning model. Many researches are based on this theory and did more innovation and improvement . Except the original model to Logistic Regression Credit Rating Model, with one or two defined variables by myself to test the warning chances, and then comparing them with the Bank Ratings Model. Finally considering under early warning correct rate, traditional Altman model was still the best. Type II and type I error in the variables that cannot be effectively decreased.

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十六卷第二期