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研究生: 余忠祐
Yu, Jung-you
論文名稱: 應用資料包絡分析法與決策樹建構共同基金選購模型之研究
Applying Data Envelopment Analysis and Decision Tree to Build up a Model for Mutual Fund Selection
指導教授: 利德江
Li, Der-Chiang
吳植森
Wu, Chih-Sen
學位類別: 碩士
Master
系所名稱: 管理學院 - 工業與資訊管理學系碩士在職專班
Department of Industrial and Information Management (on the job class)
論文出版年: 2009
畢業學年度: 97
語文別: 中文
論文頁數: 60
中文關鍵詞: 資料包絡分析法共同基金決策樹
外文關鍵詞: Mutual fund, Data envelopment analysis, Decision Tree
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  • 本研究主要目的是結合資料包絡分析法與決策樹規則運算應用於基金選購模型建立,希望可以透過實證模型的研究了解結合兩運算法則於國外基金的適用性,並找出篩選基金的重要屬性,以提供投資人評估共同基金持有組合另一個簡單的決策法則。本研究的範疇為國外四大種類基金,基金績效指標的資料來源為富盈財務資料庫;此外,基金淨值則由台灣經濟新報資料庫取得,而前期利用資料包絡分析法獲得各基金效率值使用工具為Frontier Analyst;後期決策樹模型的建構及其後樣本外的模擬則使用WEKA軟體做為分析的工具。本研究共提出兩個模型:依總體經濟的不同可分為多頭模型及空頭模型。多頭模型與空頭模型的樣本期間為2006年6月到2009年2月,分為樣本內及樣本外兩部分,樣本內(訓練組)的部分進行模型的建構,而樣本外(測試組)的資料則用來測試模型分類的正確性及有效性。綜合兩個模型的實證結果,我們可以建議投資人若對於未來行情持樂觀態度或總體經濟反轉向上,可以採用多頭模型來篩選持有的投資組合;反之,若投資人看空市場或總體經濟破底向下,則建議使用空頭模型作為投資決策的準則,同時強調風險的控管與報酬的追求,都可以篩選出同類型中在未來表現較好的基金群組。透過本研究樣本外期間分類正確率及投資報酬率的模擬,顯示具顯著性的績效指標的確可以篩選出未來報酬率較好的基金群組,證實結合DEA與決策樹所建構的模型有一定的成效,值得進一步的研究與應用。

    The purpose of this research is to build up a model for mutual fund selection by combining Data Envelopment Analysis (DEA) and Decision Tree. It is expected to understand the suitability for combining these two operation on oversea mutual fund through experiment model study, and then to offer another simple decision rule to investor for holding combination on mutual fund. The range in this research is limited to four kinds of the overseas mutual fund. The data base for the fund performance evaluation index is acquired from Folion Financial Technology Co., Ltd., and net value of mutual fund is adopted from Taiwan Economic Journal Co., Ltd. The first step is to gain the efficiency of fund by DEA with Frontier Analyst. The later period is to build up a model of decision tree with WEKA software. The research finally proposes two models, including bull model and bear model varied with macroeconomic situation. The sample period is from June/2006 to Feb/2009. The sample is composed of training data and test data. The train data can be built up the model, and the test data can be used to confirm the accuracy of model. This research suggests that investor can apply for the bull model about fund holding combination when the economic grows up in the future. Oppositely, the bear model is used as economic declines. These two models also emphasizes both risk control and profit aspiring. In addition, this research discovers the best funds from the inside of overseas mutual fund. The significance performance evaluation index can be used to discover the best funds from the inside of overseas mutual fund by the model simulation conducted in this research. The model of combining DEA with Decision Tree thus is effective in selecting fund.

    目錄 第一章 緒論 1 1.1 研究背景與動機 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 決策樹模型簡介 6 2.2 資料包絡分析法簡介 13 2.3 基金選購模型探討 23 第三章 研究架構與方法 27 3.1 研究架構 27 3.2 模型的參數介紹與分類說明 28 3.3 研究設計 33 3.4 研究方法 35 第四章 實證結果與分析 38 4.1 基金之績效分析 38 4.2 決策模型建構 39 4.3 評估決策模型分群的有效性 51 4.4 小結 52 第五章 結論與建議 54 5.1 結論 54 5.2 後續研究與建議 56 參考文獻 57

    參考文獻
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