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研究生:謝錫宗
研究生(外文):Si-Zong Sie
論文名稱:以類模糊羅吉斯迴歸預測企業違約之研究
論文名稱(外文):A Fuzzy Logistic Regression Approach to Forecast Financial Distress
指導教授:林萍珍林萍珍引用關係柯博昌柯博昌引用關係
指導教授(外文):Ping-Chen LinPo-Chang Ko
學位類別:碩士
校院名稱:國立高雄應用科技大學
系所名稱:資訊管理系
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:中文
論文頁數:69
中文關鍵詞:類模糊羅吉斯迴歸預測模型模糊理論羅吉斯迴歸
外文關鍵詞:Credit AssessmentLogistic RegressionFuzzy
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隨著金融商品創新以及自由化所帶動的經濟脈動朝向全球化發展,金融事件引發的風險將會影響全世界的金融市場。2008年的次貸風暴造成了全美為數不少的保險與銀行陸續宣告破產,至今為止已造成美國40家銀行倒閉,連帶也影響到全世界的證券市場大幅修正與景氣蕭條。而這些事件發生的原因,都與金融機構對信用風險評估不當有關。以銀行為例,信用風險的大宗是企業授信,放款業務則是銀行主要的獲利來源,銀行也隨之發展出信貸相關制度,管控信貸造成的呆帳問題,由於企業放款金額相當龐大,故企業的違約風險管理就顯得相當重要。Basel II更以內部評等法為基礎,違約機率為預測系統的主要考量核心。在一般傳統統計方法中,羅吉斯迴歸是最常被使用的統計分類技術,然而真正的衡量重點在於變數的模糊與不確定性。因此本研究提出一種模糊的羅吉斯回歸,利用模糊理論的定義將變數轉換為模糊定義值,建立類模糊羅吉斯迴歸預測方法。最後再以準確性、穩定性等測試比較。其實驗結果顯示,模糊羅吉斯在誤差值或離群值較多的狀況中,預測準確率與預測效力均較佳於羅吉斯迴歸方法。
De to the innovative financial products and financial globalization, the financial events would have deep impact in global financial markets. The well-known financial tsunami: American sub-prime mortgage has sent shockwaves throughout the whole world over the past few days. It causes many banks, corporations and even governments scramble to cope with various serious downturns in the major economies. The loan growth, especially in the enterprise loans, is one of major profit for banks. It is important to manage and evaluate corporate financial risk effectively, because inaccurate credit rating for business leads to the more serious financial crises. The well-known Basel II published in June 2004 allows banks to assess the key risk drivers as the primary capital calculation, which establishes regulatory expectations for credit risk through the Internal Ratings Based (IRB) approach. In conventional statistical methodology, the logistic regression is commonly used with selected variables from financial statements for probabilistic binary classification. However, the real values of financial variables are fuzzy and uncertainty values generally. In this paper, a fuzzy-based logistic regression (FLR) model is introduced to study the effect of knowledge translation in fuzzy approximation spaces in credit risk evaluation, where the crisp values of financial variables are translated to fuzzy numbers, and the logistic regression is modified by fuzzy operation. The final experimental results show that FLR provides better performances in classification accuracy and early warning capabilities.
摘要 1
Abstract 2
目錄 4
表目錄 7
圖目錄 8
第一章 緒論 10
第二章 文獻探討 13
2.1 羅吉斯迴歸模型(Logistic Regression Model, LR) 13
2.2 模糊理論(Fuzzy) 14
2.2.1 模糊集合(Fuzzy Sets) 16
2.2.2 模糊運算(Fuzzy Arithmetic) 18
2.2.3 解模糊化(Defuzzification) 21
2.3 企業違約風險預測模型 23
2.3.1 企業違約風險預測因子 23
2.3.2 企業違約風險預測模型 25
2.4 整合Fuzzy與迴歸模型 26
2.4.1 模糊迴歸分析相關文獻 26
2.4.2 模糊迴歸其它領域的應用 27
第三章 研究架構 29
3.1 研究架構 29
3.2 最大概似估計法 31
3.3 方程式解模糊化 32
3.4 牛頓法(Newton's method) 34
3.5 效力驗證方法 36
3.5.1 CAP(Cumulative Accuracy Profiles)曲線 36
3.5.2 ROC(Receiver Operating Characteristic)曲線 37
第四章 實驗設計與結果 41
4.1 資料前置處理 41
4.3.1 資料來源 41
4.3.2 樣本變數 41
4.3.3 資料定義 42
4.3.4 資料處理 44
4.2 實驗設計 44
4.3 實驗結果 45
4.3.1 實驗一:「潘秋梅(2006)[37]」建議指標準確率比較 46
4.3.2 實驗二:「游俊忠(2008)[36]」建議指標準確率比較 47
4.3.3 實驗三:「游俊忠(2008)[36]」建議指標預測效力驗證 48
第五章 方法開發工具及操作過程說明 52
5.1 開發工具與環境簡介 52
5.2 方法操作說明 52
第六章 結論與建議 55
6.1 結論 55
6.2 未來建議 56
參考文獻 57
附件 62
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