信用風險模型的發展隨著資產證券化與信用衍生性金融商品的推陳出新，從評估單一實體的違約機率，發展到需要估計多個實體間的違約相關性，但用來估計違約相關性中最常討論到的方法，是使用結構法模型結合Copula函數來估計，因此，Jarrow and Deventer在2005年提出使用縮減法中危險率概念的Logistic模型， 來估計公司間的違約相關性，避免在使用結構法及Copula函數所遇到的問題。故本文即以該模型為實證架構，測試在國內上市公司資料下，除了使用會計、市場變數， 另外再增加總體經濟變數，看是否可以得到一個最佳的預測違約機率模型，且驗證此違約相關模型是否能合理地描述國內上市公司間的違約相關情形， 最後，測試該模型評價擔保債權憑證分券信用價差的可行性，看是否能合理的捕捉到違約風險的衡量。
經實證結果發現，多加入總體經濟變數後，此危險率概念的Logistic模型預測能力果然有增加，違約機率的預測確實與公司體質、市場及總體經濟因素有關。而違約相關性的實證也得到，該模型可以估計出符合國內上市公司違約相關的情況，違約事件同時發生(在同一年)的主因是公司經營狀況的共同點，並非共同的總體因素。最後，該模型可以合理地估計出擔保債權憑證分券信用價差，驗證該模型在違約風險的衡量上是可行的。

With the weeding out the old and bringing forth the new of assets securitization and credit derivatives, the development of the credit risk models is from estimating the default probability of single entity to default correlation of multi-entities.The most discussed approach for estimating these default correlations is to use a structural model in conjunction with a copula function. Therefore, Jarrow and Deventer used a reduced-form model to estimate default correlations in 2005. It can avoid the problem of structural model in conjunction with a copula function. So this thesis tests it under the data of Taiwan listed company. In addition to accounting、market variables, I add macroeconomic variables to get a best prediction model of default probability. I also investigate whether this default correlation model can reasonably descript default correlation of Taiwan listed company. Finally, I tests feasibility of this models for evaluating credit spread of collateralized debt obligation.
From the empirical result, when adding macroeconomic variables, the prediction capacity of logistic model with hazard rate concept surely increase. The prediction of default probability truly has something to do with business entity、market and macroeconomic factors. Furthermore,
from the empirical results of default correlation, the model can estimate the situation of default correlation which conforms to Taiwan listed company. Eventually, this model can reasonably estimate credit spread of collateralized debt obligation and it is feasible to measure default risk with this model.

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