淡江大學機構典藏:Item 987654321/31702
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62822/95882 (66%)
Visitors : 4028263      Online Users : 570
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/31702


    Title: 公司信用風險之衡量 : 以財務比率與選擇權評價法為例
    Other Titles: Predicting corporate financial distress-using financal ratio and down-and-out call framworks
    Authors: 黃景鋒;Huang, Ching-feng
    Contributors: 淡江大學財務金融學系碩士班
    林允永;Lin, Yun-yung
    Date: 2005
    Issue Date: 2010-01-11 01:09:03 (UTC+8)
    Abstract: 判斷公司違約風險的大小是風險管理重要的一環,管理者利用各種模式評估公司的信用狀況。本研究以統計模式構建組合預測,期望能簡化管理者的決策過程。本文先分別以逐步迴歸法及因素分析法選取財務比率變數並應用Logit模型建構危機發生前一年及前二年之財務危機預警模式,除傳統財務比率變數外,另外再加入選擇權評價法的違約機率值,檢視模型之正確區別率是否能顯著提高。
    根據實證結果,在危機發生前一年,以信用風險模型的正確區別率最低,而在財務變數為預測變數方面,不管是危機發生前一年或前兩年,利用逐步迴歸法選取財務變數的預測正確率優於採用因素分析法,但不論選取財務變數的使用方法為何,若與信用風險模型的違約機率合併做組合預測,皆能使正確歸類率改善,說明組合預測能改善單一指標對公司的違約預測。
    It is an important part of risk management to assess company''s credit risk. The administrator use various kinds of ways to assess the credit condition of the company, but different ways may produce different results. This paper structures a portfolio by statistical method, expect to be able to simplify the administrator''s decision-making process. First separately with stepwise regression analysis and factor analysis choose financial rate parameter and use Logit model to construct the financial distress model in the previous year and the first two years take place in the crisis. Besides traditional financial rate parameter, accede to the default probability value of the option pricing method in addition, to observe whether these variables make the construction of financial distress model better accordingly.
    According to the reserch result , take place in the previous year in the finance distress, the correct difference rate of the credit risks model is the lowest. And the distress takes place in the previous year or the past two years, the correct rate of prediction of utilizing stepwise regression analysis to choose the financial parameter is superior to adopting the factor analysis. No matter with which kind of method chooses the financial parameter, if combine with the default probability value, we can get the better correct rate .
    Appears in Collections:[Graduate Institute & Department of Banking and Finance] Thesis

    Files in This Item:

    File SizeFormat
    0KbUnknown243View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback