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博碩士論文 etd-0723107-201804 詳細資訊
Title page for etd-0723107-201804
論文名稱
Title
信用風險衡量 結構式模型KMV-EDF於台灣電子產業上市公司之研究
Credit Risk Valuation:.A Research with the KMV model -EDF for Taiwan Electronic Companies
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
106
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2007-06-14
繳交日期
Date of Submission
2007-07-23
關鍵字
Keywords
違約距離、市場基礎、KMV模型、違約機率
KMV model, Expected Default Frequency, market-based, Distance to Default
統計
Statistics
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中文摘要
摘 要
自 1980 年代起在金融自由化以及資訊科技快速發展衝擊下,金融市場蓬勃發展,特別是衍生性金融商品之相繼問世,促使金融機構業務與交易型態多元化,此金融現象相對地增添了新的風險與不確定性,更帶來了日益複雜的信用風險型態,致使市場參與者原有風險衡量工具,風險結構與信用文化均遭受到嚴苛的挑戰,尤其在 1990 年代國際間陸續發生多起金融危機或弊案,財務風險管理遂成為政府、金融機構、與投資大眾關心的議題。
財務風險中「信用風險」一直是風險管理的聚焦,特別是國際清算銀行(Bank for International Settlements, BIS)所屬巴塞爾銀行監理委員會(Basel Committee on Banking Supervision),所公布新版巴塞爾資本協定( The New Basel Capital Accord ,或稱 Basel II) ,不僅對信用風險賦予重視外,更允許金融機構發展內部評等模型( Internal Rating Based Approach, IRB) 以計提適當之風險性資本。此措 施使得信用風險評量模型的研發亦成為產、官、學界所關注的焦點。
自Merton (1974)將選擇權評價模式運用在衡量企業信用風險技術上,受歐美學術界與實務界的重視。此模式是結構式模型的理論基礎,目前實務上著名之KMV 模型,即是莫頓模型的延伸與應用,除具備嚴謹理論外,並將市場資訊股價資訊變為衡量信用風險之重要變數,使信用風險可採取高頻率即時監控,廣為後續學術界與實務界應用。
本研究基於(1)信用風險具有地區或文化特性,由國外引入信用風險衡量模式,亦需因地制宜,更需本土理論與實務研究之實證支持,(2)結構法屬 look forward分析法,具有市場基礎(market-based)資訊內涵,(3)經審慎考量國內資本市場情況,國內電子產業為台灣資本市場最大類股,也是台灣在國際上最具有競爭力之產業,但此產業在獲利、成長與風險三構面卻具有高度之產業敏感度。遂以 2004年到2006年,最近三年台灣電子產業所有上市公司為研究對象,進行整體產業與個別產業之預期違約機率(Expected default frequency簡稱EDF)之研究。同時參考郭照榮(2006)之中小企業信用保證基金主要保證業務之違約機率與信用風險評估之研究報告,於變數定義與選取賦予慎密考量,力求合於穩健原則及兼顧經濟實質意義,經實證結果,發現對台灣電子產業而言, KMV模型之EDF可獲致顯著性風險評估效果及發揮EDF之預警效果。
本文貢獻在於能提供研究結果予從事信用風險管理者供參,使債權人、投資者及政府機關能瞭解企業涉險程度,進而作出有效的投資策略與風險管理方法,以達到徵信成本與融資企業資金成本之最小化,管理效率與投資效益之最大化。
Abstract
Abstract
Ever since 1980, facing the impact of the more freedom of trading market and the fast developing on the new technology, financial market grows rapidly in prosperity. Especially the derivative financial goods are brought to the market, the financial organization’s affairs and trading styles become more diversified, also added new risks of uncertainty. Furthermore, more complicated credit risk patterns caused the traditional measuring tools of financial risk among market participants, even risk structure and credit culture being severely challenged. During 1990, financial crisis or fraud cases consecutively happened in the international financial market, so the financial risk management has become a subject concerned by financial organizations, government and the public investors.
However, credit risk is always the focus in all the financial risks. Especially the Basel Committee on Banking Supervision, (a branch of the Bank for International Settlements, BIS), published “The New Basel Capital Accord” (Basel II). In this New Basel Capital Accord, it not only emphasizes the importance of credit risk, but also allows financial organizations to develop Internal Rating Based Approach, “IRB” to evaluate and calculate proper risk capital. These operations for credit risk evaluation model’s development have been focused on the academic circle, government, and business circle.
Since Merton (1974) has applied options pricing model as a technology to evaluate the credit risk of enterprise, it has been drawn a lot of attention from western academic and business circles. Merton’s Model is the theoretical foundation of structural models. Currently, the famous KMV Model in practically is the extension of application of Merton’s Model. Merton’s model is not only based on a strict and comprehensive theory but also used market information stock price as an important variance to evaluate the credit risk. This makes credit risk to be a real-time monitored at a much higher frequency. This advantage has made it widely applied by the academic and business circle for a long time.
According to this research topics: (1) Credit risk holds geographical and culture character. Though credit risk evaluating model introduced from the foreign, yet it still has to be modified locally and it also needs more supports from local theory and practical case study. (2)Structural model is based on “look-forward” analysis. It implies market-based information contents. (3) After prudent and careful analytical consideration about domestic capital market, the electronic business is the mainstream of domestic stock market, and also the competitive business for Taiwan in the world, meantime, electronic business has a higher level of sensitivity in three phases of profit, prosperity and risk. So that, I choose electronic companies in the public stock market as my research target and time frame is across 2004 to 2006, by means of KMV model which is a mainstream of structural model to evaluate credit risk, developed by Moody’s Co. USA. I also referred to “Small and Medium Enterprise Credit Guarantee Fund Main Guarantee Business Default Probability and Credit Risk Valuation Research Report”, authored by C. J. Kuo (2006) for the variable definition and selections giving very thorough considerations. As I proceed a series of research in using EDF (Expected Default Frequency) of KMV model as well as a number of empirical investigation procedures in integrity and individual electronic business. I find out that EDF of KMV model it can obtain the prominent effect in credit risk and the prediction ability in advance.
This paper can provide research result as a reference to risk-manager and to assist investors and governor to discern the depth of risks that the enterprise involved and then to decide the policy of strategy investment and level of risk management. Eventually to minimize the cost of credit checking and enterprise capitals, while to maximize the managerial efficiency and the profitability is the contribution of this paper could be.
目次 Table of Contents
目 錄
第一章 緒論 1
第一節 問題背景與資料觀察1
第二節 研究目的5
第三節 研究架構與流程6
第二章 主要文獻回顧與探討8
第一節 信用風險模型之發展與文獻探討8
第二節KMV模型與相關文獻探討23
第三章 研究方法34
第一節 研究期間對象與資料來源34
第二節 實證模式及研究設計35
第四章 實證結果與分析45
第一節 整體電子產業分析與檢定45
第二節 個別電子產業分析與檢定50
第五章 結論與建議71
第一節 結論71
第二節 建議71
參考文獻74
附 錄一個別電子產業敘述統計及直方圖78
附 錄二台灣證交所電子產業分類表85
附 錄三電子產業所有上市公司實證預估之違約距離與違約機率表88
參考文獻 References
1.王懷德(2003),「KMV模型於國內未上市、未上櫃之公開發行公司之研究」,東吳大會計學系研究所。碩士論文。
2.毛盛杰(2006),「新巴塞爾協定對銀行經營效率的影響以三大風險為例」,東吳大學經濟學系碩士論文。
3.李欣怡(2005),「以KMV修正模式探討台灣上市櫃公司違約風險」,東華大學國際經濟研究所,碩士論文。
4.李明峰(2001) ,「銀行業對企業授信『信用評等表』財務比率預警有效性之實證分析」,中山大學財務管理學系研究所
5.阮懷勝(2006),「財務危機預警模式之研究-以電子產業為例」,東吳大學會計學系碩士論文。
6.周培如(2004),「銀行危機預警指標-KMV 信用風險模型與財務指標之應用」,國立政治大學經濟學系碩士論文
7.郭照榮(2005),「金融環境與現代風險管理的新思維」,第一商業銀行風控研訓計畫講義,國立中山大學金融管理研究中心。
8.郭照榮等人(2006),「中小企業信用保證基金主要保證業務違約機率與信用風險評估」,中小企業信用保證基金委託研究報告。國立中山大學金融管理研究中心。
9.黄仁德、陳淑郁(2005), 信用風險衡量理論與實務,財團法人中華民國證券暨期貨市場發展基金會。
10.黃建隆(2003),「以市場模式衡量信用風險」,文化大學會計研究所碩士論文。
11.黃繼寬(2005),「考慮產業差異下信用評分模型效力分析」,東吳大學經濟學系碩士論文。
12.陳達新、周恆志(2006),財務風險管理-工具、衡量與未來發展,雙葉書廊有限公司。
13.陳錦村(2004),「風險管理概要-個案與實務」,新陸書局股份有限公司。
14.陳思翰(2003),「商業銀行如何利用logit 及KMV模型檢視授信政策」,中央大學財務金融研究所碩士論文。
15.莊傑富(2005),「不同信用評分模型對信用評等之影響」,東吳大學經濟學系碩士論文。
16.Crouhy .Galai .Mark(2004),風險管理,台灣金融研訓院編譯委員會譯,台灣金融研訓院傳播出版中心,美商麥格羅 希爾國際股份有限公司 台灣分分公司。
17.Altman, E.I., (1968),“Financial Ratios, Discriminant Analysis and the Rediction of Corporate Bankruptcy” , Journal of Finance, 23(4),pp.578-609.
18.Beaver, W. H., (1996),” Financial Ratios as Predictors of Failure. ,Empirical Researchin Accounting: Selected Study, Journal of ccounting Research (Supplement)” ,pp. 1966:77-111.
19.Altman E. I., R.G. Haldeman and P. Narayanan, “ZATE Analysis-A New Model toIdentify Bankruptcy Risk of Corporations. ” Journal of Banking And Finance. Vol. 1, June 1977:29-54.
20.Blum,M.Spring (1974),“Failing Company Discriminant Analysis” Journal Of Accounting Research, pp.1-25.
21.Crosbie, J, Peter 1999, “Modeling Default Risk”, KMV: San Francisco, California, U.S.A.
22.Kealhofer, S., 1998. “Portfolio Management of Default Risk” KMV corporation, 11-February.
23.Jeffrey, R. Bohn, 1999, “Using marketing data to value credit risk instruments”, KMV corporation, 27-Sept.
24.Gentry, J. A., P. Newbold and D. T. Whitford , Classifying Bankrupt Firms with Funds Flow Components. Journal of Accounting Research. Vol.23, No 1,1985:146-160
25.Ohlson, J. ( 1980 ),“Financial Ratios and the Probabilistic Prediction Of Bankruptcy”, Journal of Accounting Research, 19, 109–131.
26.Black, F., and M. Scholes (1973),”The Pricing of Options and Corporate Liabilities”, Journal of Political Economy Vol.8, No.3, pp.637-653.
27.Merton, R. C.(1974),”On the Pricing of Corporate Debt : The Risk Structure of Interest Rates”, Journal of Finance, Vol.29, No.2,
pp.449-470.
28.Martha, S and Alexis, D, 1997, “Modeling Default Risk: Private Firm Model”KMV: San Francisco, California, U.S.A.
29.Mikael, N, Martha, S and Jing, Z, 2001, "Private Firm Model, Introduction to the
modeling methodology” KMV: San Francisco, California, U.S.A.
30.Christopher C. Finger , Vladimir Finkelstein , George Pan , Jean-Pierre Lardy , Thomas Ta and John Tierney , 2002 , "CreditGrades™ Technical Document, “
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