王泰昌臺灣大學:會計學研究所陳彥翰Chen, Yen-HanYen-HanChen2007-11-282018-06-292007-11-282018-06-292004http://ntur.lib.ntu.edu.tw//handle/246246/61815自1998年第四季到2001年第四季,我國有釵h上市上櫃公司發生財務危機,造成公司的員工、客戶、供應商、債權人、股東均蒙受巨大損失。因此,本研究的目標在於建立有效的違約機率預測模型,量化公司信用風險以提供管理當局、投資人、債權人或其他公司關係人決策所需的資訊。 本研究利用logistic 離散涉險模型(logistic discrete hazard model)建立違約機率預測模型,並使用精準度(accuracy ratio) 與Vuong test比較模型的優劣。主要的實證結果如下: 一、本研究採用的各種模型(包括:會計比率模型、市場變數模型、違約間距模型)的相對預測能力在電子業、營建水泥業、其他各業,並不相同。 二、關於本研究的四類解釋變數:會計比率、市場變數、總經變數、股權變數,本研究發現預測能力較低之解釋變數在釵h情況下仍然具有預測能力較高之解釋變數所沒有的資訊,亦即具有增額資訊的效果。 三、本研究發現包含四類解釋變數之合併模型的精準度(accuracy ratio)幾乎都高於個別模型的精準度,只有在營建水泥業之某種違約定義下,合併模型的估計樣本外精準度(out-of-sample accuracy ratio)略低於會計比率模型。From the fourth quarter of 1998 to the fourth quarter of 2001, many listed and over-the-counter corporations in Taiwan have fallen into financial crises, resulting in huge losses to the employees, customers, vendors, debt holders, and stockholders. The purpose of this thesis is to build an effective model which predicts default probability and quantifies credit risk for information needed by the management, stockholders, debt holder, or other related persons in decision use. This thesis uses logistic discrete hazard model to predict default probability, and evaluates the performance of models with the concept of Accuracy Ratio and Vuong test. The major research findings are as follows: I.The relative predictive power of the accounting ratios model, the market variables model, and the default distance model is not the same for the electronic industry, construction and cement industry, and the rest of others. II.With respect to the four types of explaining variables: accounting ratios, market variables, macroeconomic variables, and stockholding variables, it is found that in many cases the types with inferior predictive power contain incremental information relative to the best one. III.It is found that the accuracy ratios of the combined models including the four types of explaining variables are higher than those of the separate models including only one type of explaining variable, except under my first definition of default in the construction and cement industry, in which case the out-of-sample accuracy ratio of the combined model is slightly lower than that of the model of accounting ratios.第一章 緒論................................1 第一節 研究動機與背景....................1 第二節 研究目的..........................1 第三節 論文架構..........................2 第二章 文獻回顧............................3 第一節 信用風險模型的研究及發展..........3 第二節 Logistic Discrete Hazard Model.. 11 第三節 選擇權模式的信用風險衡量模型.....13 第四節 總體經濟變數.....................16 第三章 研究方法...........................18 第一節 估計模型的選擇...................18 第二節 可能的解釋變數...................18 第三節 研究範圍及資料來源...............26 第四節 預測能力的比較方式...............28 第五節 篩選變數.........................33 第四章 實證結果...........................36 第一節 會計比率.........................36 第二節 市場變數.........................42 第三節 總經變數.........................53 第四節 股權變數.........................57 第五節 全部變數.........................60 第五章 結論與建議.........................77 第一節 結論.............................77 第二節 研究限制與建議...................79805425 bytesapplication/pdfen-USlogistic 離散涉險模型信用風險精準度credit riskaccuracy ratiologistic discrete hazard modelLogistic Discrete Hazard Model在信用風險上之應用The Application of Logistic Discrete Hazard Model to Credit Riskotherhttp://ntur.lib.ntu.edu.tw/bitstream/246246/61815/1/ntu-93-R91722012-1.pdf