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論文中文名稱:整合KMV模型、約略集合及隨機森林應用於企業信用評等之研究 [以論文名稱查詢館藏系統]
論文英文名稱:A study on integrated KMV model, rough set and random forest for firm’s credit ratings. [以論文名稱查詢館藏系統]
院校名稱:臺北科技大學
學院名稱:管理學院
系所名稱:商業自動化與管理研究所
畢業學年度:98
出版年度:99
中文姓名:許智宇
英文姓名:Chih-Yu Hsu
研究生學號:97488049
學位類別:碩士
語文別:中文
口試日期:2010-06-04
論文頁數:77
指導教授中文名:林鳳儀
指導教授英文名:Fengyi Lin
口試委員中文名:葉清江;黃俊閎;趙莊敏
口試委員英文名:Chin Chiang Yeh;Chun Hung Huang;Chuang Min Chao
中文關鍵詞:信用評等KMV模型隨機森林約略集合
英文關鍵詞:Credit ratingsKMV modelRandom forestRough set
論文中文摘要:近年來許多企業雖然擁有較高的信用等級,卻遭受整併或倒閉,因此提供一個有效的信用評等模型是個重要的議題。為解決此問題,本研究利用整合隨機森林與約略集合進行兩階段分類模式的企業信用評等評估模型。此外,在探討信用評等的衡量指標上,本研究參考過去文獻與研究所使用財務性變數之外,亦加入KMV模型的違約距離變數與公司治理等變數建構模型,希望能藉由更完整多元的資訊,來幫助企業本身評估其信用評等,並做出正確的決策。本研究經由理論與文獻的探討,建立了新的信用評等模式,在經過實證的結果發現,經由隨機森林方法針對所考量之衡量信用評等指標進行分析,得知企業的信用評等,除了受到傳統財務變數的影響外亦受到違約距離與公司治理等變數的影響。其中,違約距離在影響信用評等分類結果的重要性高於公司治理變數。再者,有關整合隨機森林與約略集合方法所建構之信用評等模式亦能確實提升信用評等的準確率之外,透過約略集合導出的決策規則亦可提供授信人員作為企業信用評等決策依據。
論文英文摘要:The development of the firm’s credit rating prediction model has attracted lots of research interests in academic and business community. The objective of this proposed study is to investigate the performance of firm’s credit ratings with random forest and rough set technique. In addition to traditional financial indicators, KMV and corporate governance variables are also included in this model. As the results reveal, we find out traditional financial indicators, default distance and corporate governance variables significantly influence the diagnostic accuracy of firm’s credit ratings by applying our proposed approach. Moreover, our present study indicates that the proposed integrated approach predicts more accurate than solely adopting rough set technique. In the other words, by adopting random forest approach to come out with good initial estimation, rough set approach might takes longer time to achieve accurate results. Finally, we believe the credit rating rules we had summarized in this study could further assist investors’ decision making.
論文目次:摘要 I
ABSTRACT II
誌謝 III
目錄 IV
圖目錄 VII
表目錄 VIII
第一章 緒論 1
1.1 研究動機 1
1.2 研究目的 3
1.3 研究範圍 4
1.4 研究架構 4
第二章 文獻探討 6
2.1信用風險與評等模型 6
2.1.1巴塞爾協定信用評等內容 7
2.1.2 信用評等方法 9
2.2 國內外信用評等模型 10
2.2.1信用評等相關研究 14
2.3 KMV模型文獻探討 16
2.4 公司治理 19
2.4.1 公司治理與信用評等 20
2.5 決策樹 22
2.6 隨機森林 23
2.7 約略集合 25
第三章 研究方法 27
3.1 觀念性架構 27
3.2研究變數選取 28
3.3 KMV模型 31
3.4 兩階段分類模式 33
3.4.1 特徵選取 33
3.5 隨機森林 34
3.5.1 隨機森林進行特徵選取 37
3.6 約略集合 38
3.7 決策樹C 5.0 40
第四章 實證研究 41
4.1本研究變數敘述統計 41
4.2 KMV模型分析 43
4.3 隨機森林分析 43
4.4 整合隨機森林與約略集合分析 49
4.5決策規則分析 55
第五章 結論與建議 59
5.1結論 59
5.2 研究貢獻 61
5.3 建議 62
第六章 參考文獻 63
一、中文部份 63
二、英文部份 64
附錄 73
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論文全文使用權限:同意授權於2012-07-27起公開