本文應用Duan et al. (2012)發展之遠期強度模型(Forward intensity model)，針對台灣上市櫃公司1992年至2020年的財務會計變數及違約月資料預測公司遠期違約機率，該模型優勢為使用最新且可取得的資料預測公司遠期違約機率，因此在計算上較容易，且結果更為穩健。衡量模型預測準確度的方法為AUC值與Z檢定的分析，將遠期強度模型預測結果與KMV模型比較預測績效，發現在一年、兩年、三年之樣本外區間，兩模型於本文選取之大部分產業的預測違約表現並無顯著差異。

This study applied the forward intensity model developed by Duan et al. (2012) to predict the default probability of listed companies in Taiwan, spanning the period 1992–2020 based on a monthly based financial accounting variables and default data. The advantage of this model is that it utilized the latest and accessible data to predict the company's long-term default probability. Therefore, it is easier to calculate and the result is more robust. The methods used in analyzing the models’ prediction accuracy are AUC and Z-test. We compared the prediction performance between the forward intensity model and KMV model, and we found in one-year, two-year and three-year out-of-sample intervals, there is no significant difference in prediction performance between these two models in most industry we selected in this study.

論文審定書 i
摘要 ii
ABSTRACT iii
目錄 iv
圖目錄 vi
表目錄 vii
1. 緒論 1
1.1 研究背景 1
1.2 研究目的 2
1.3 研究架構 2
2. 文獻回顧 3
2.1 專家系統 3
2.1.1 類神經網路分析法 3
2.2 內部評等法 4
2.3 信用評分模型 5
2.3.1 線性迴歸機率模型 5
2.3.2 Logit model and Probit model 6
2.3.3 多變量區別分析 6
2.4 公司財務危機定義 8
3. 資料來源與研究方法 10
3.1樣本選取及資料整備 10
3.1.1 遠期強度模型使用變數 11
3.1.2 KMV模型使用變數 12
3.2 研究方法 13
3.2.1遠期強度模型 13
3.2.2 KMV模型 15
3.3 預測績效評估指標 16
3.3.1 ROC曲線 16
3.3.2 Z檢定 18
4. 實證結果 19
4.1 遠期強度模型預測實證結果 19
4.1.1 樣本外各產業預測結果 20
4.2 模型預測結果比較 21
5. 結論與建議 22
5.1 結論 22
5.2建議 23
參考文獻 24

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