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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/31479

    Title: 企業授信運用信用評分及選擇權評價之有效性分析
    Other Titles: The analysis of effectiveness on corporation loan using credit scoring and option pricing
    Authors: 黃明珠;Haung, Ming-chu
    Contributors: 淡江大學財務金融學系碩士在職專班
    陳達新;Chen, Dar-hsin
    Keywords: 信用分數;選擇權評價;財務危機預測模型;logistic迴歸分析;檢定力曲線;Credit Scoring;Option Pricing;Financial Distress Forecasting Model;Logistic Regression;Power Curve
    Date: 2006
    Issue Date: 2010-01-11 00:47:33 (UTC+8)
    Abstract: 台灣地區商業銀行因企業為邁向國際化,從事高桿槓財務操作,其融資動機不似以往單純。辦理企業授信倘仍依循專家經驗主觀判斷,對企業營運及財務異常現象將無法即時掌握。為此,本研究利用Altman(1968)的Z-Score信用評分及KMV選擇權模型作為衡量信用風險評估工具。惟本研究在KMV模型之違約點細分為違約點1=公司負債總額;違約點2=公司短期負債;違約點3=公司短期負債+1/2長期負債,分別求出預期違約機率,作為兩模型在財務危機企業預測之比較。
    Since many corporations in Taiwan operate higher financial leverage to become globalizing enterprises, the purposes of applying loan aren’t as simple as before. If banks approve corporation loans based on specialists’ experience, they will unable to detect the credit risk of these companies in time. Therefore, this paper applied two models to measure the credit risk: “ Altman’s Z-Score (credit scoring)and KMV option model(option pricing).” However, we defined the default point as point 1= the total debts; point 2= the short term debts and point 3= the short term debts +1/2 the long term debts to individually figure out the Expected Default Frequency .
    Using the data from 73 financial distressed Taiwan’s listed companies from 2000 to 2005, and used the 1:1 matching sample method to select data from similar companies to contrast. Then, we adopted two major comparative laws: logistic regression and power curve. The empirical results of two kinds of comparative methods all get the same conclusion that KMV option model is significantly better than Z-score. Moreover, it can provide a concise, scientific and objective verifying standard as another model to measure and manage the credit risk for banks in Taiwan.
    Appears in Collections:[財務金融學系暨研究所] 學位論文

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