臺灣博碩士論文加值系統

傳統上基金投資的優點在於透過投資組合可分散風險以及有專業的研究團隊與操作經理人執行操盤，Kacperczyk, Sialm, and Zheng（2005）提出基金集中投資可為投資人帶來的價值比分散投資多，並以產業集中度為量測指標，爾後陸續有學者提出以產品、集團、個股、持有家數等不同層面探討分散投資與基金績效之間的關聯性，故本文也採取上述五種集中度的量測指標來作為研究之變數。而集中投資必定帶來高波動的報酬程度，所以本文之貢獻在於評估績效上除了報酬亦納入報酬之變異數及偏態係數做線性規劃模式，以評估出較佳的基金相對效率值，而因相對效率值之最大值為1，此為受限制資料，再使用受限制的迴歸模型來做探究，並且本研究認為基金集中投資與否，並非為單一方向的關係，一味地分散投資組合或集中投資，故使用受限制分位數迴歸來分析在不同的績效區間，其集中度量測指標與基金績效間的關係。本研究以144檔台灣境內股票型基金2005至2009年為期間，結果顯示以平均狀況而言，集中度指標對基金績效皆無顯著的影響；而在績效最差的第10百分位區間，五種集中度指標一致顯示分散投資對績效有正向的幫助，表示績效較差的基金經理人應以分散投資組合為其操盤策略；在績效最佳的第90百分位區間，個股集中度與持股家數顯示集中投資對績效有正向的幫助，代表績效好的基金能藉由精選個股為投資人創造價值。

Traditionally, the advantages of mutual funds are the benefit of diversification and professional trading. However, it seems to have a conflict between the two advantages. A growing literature provides empirical evidences that fund managers have superior information of stocks, then they would like to hold focused portfolios to improve their performances.
The mutual fund performance measurements used in this paper is the shortage function in the mean-variance-skewness space (MVS).To solve the problem of the censored value of scores. The purpose of this study is to use the censored quantile regression model to evaluate the relationship between the concentration index and mutual fund performance under different efficiency quantile levels.
The result shows that the fund group with the highest 10% efficiency scores have the positive relationship between scores and concentration by investing in specific stocks. In the group of the worst 10% efficiency scores, the five indicators to measure the degree of concnetration in portfolio prove that diversification is the best strategy for fund managers to execute their asset allocating.

目 錄
摘　要 i
ABSTRACT ii
誌 謝 iii
目 錄 iv
表目錄 vii
圖目錄 ix
第一章 緒論 1
1.1 研究背景 1
1.2研究動機 3
1. 3 研究目的與架構 6
1.3. 1 研究目的 6
1.3. 2研究架構 7
第二章 文獻探討 8
2. 1 共同基金介紹 8
2.1. 1 共同基金的組織型態 8
2.1. 2 共同基金的分類方式 9
2.1. 3 共同基金的評等機構 11
2. 2 共同基金衡量績效方法之相關研究 11
2.2. 1傳統方式衡量績效 11
2.2. 2 DEA、SFA方式衡量績效 15
2.2. 3 MVS方式衡量績效 19
2. 3共同基金績效之影響因素 23
2.3. 1 投資組合持股家數 23
2.3. 2 投資組合集中度指標 24
2.3. 3 其它基金變數 28
2. 4 受限制分位數迴歸之相關研究 31
2.4. 1 分位數迴歸 31
2.4. 2 受限制分位數迴歸 33
2. 5 文獻總結 38
第三章 研究方法 40
3. 1 投資組合MVS空間與效率前緣 40
3. 2 短缺函數（Shortage Function）績效衡量法 42
3. 3 分位數迴歸 44
3. 4 受限制分位數迴歸 46
第四章 實證模型 47
4. 1資料來源與變數說明 47
4.1. 1資料來源 47
4.1. 2 資料期間與研究對象 47
4.1. 3 集中度指標 47
4.1. 4 其它基金變數 48
4. 2實證模型 50
4.2. 1 投組組合MVS效率評估模型 50
4.2. 2 受限制分位數迴歸模型 51
第五章 實證結果與分析 52
5. 1 基金效率值評估結果 52
5. 2基金績效與集中度變數敘述性統計 57
5. 3受限制分位數迴歸變數敘述性統計 58
5. 4受限制分位數迴歸分析結果 61
5.4. 1產業集中度與效率值 61
5.4. 2產品集中度與效率值 63
5.4. 3集團集中度與效率值 64
5.4. 4個股集中度與效率值 65
5.4. 5股票持有家數與效率值 66
5.4. 6各集中度指標與效率值關係匯總分析 67
5.4. 7集中度指標同時性分析 71
第六章 結論與建議 73
6. 1結論 73
6. 2後續研究建議 75
參考文獻 76
附錄. 1、樣本基金各期評估效率值排名 83
附錄. 2、樣本基金各期評估效率值 87
附錄. 3、產業集中度之產業分類表 91
附錄. 4、產品集中度之產品分類表 92
附錄. 5、集團集中度之產集團分類表 94
附錄. 6、個股集中度之個股分類對照表 98

表目錄

表1. 1 國內發行基金規模表 1
表1. 2 國內發行基金規模表（續） 2
表2. 1 基金名稱分類表 10
表2. 2 國內股票型基金分類定義表 10
表2. 3 傳統方式衡量績效的相關文獻整理 14
表2. 4 傳統方式衡量績效的相關文獻整理(續) 15
表2. 5 DEA、SFA方式衡量績效的相關文獻整理 18
表2. 6 MVS方式衡量績效的相關文獻整理 21
表2. 7 MVS方式衡量績效的相關文獻整理(續) 22
表2. 8 衡量投資組合集中程度的相關文獻整理 26
表2. 9 衡量投資組合集中程度的相關文獻整理(續) 27
表2. 10 其他基金變數的相關文獻整理 29
表2. 11 其他基金變數的相關文獻整理(續) 30
表2. 12 分位數迴歸的相關文獻整理 32
表2. 13 受限制分位數迴歸的相關文獻整理 36
表2. 14 受限制分位數迴歸的相關文獻整理(續) 37
表2. 15 受限制分位數迴歸的相關文獻整理(續) 38
表 5. 1 各期績效最佳基金 52
表 5. 2 各期績效最佳基金(續) 53
表 5. 3 基金類型平均績效與排名 54
表 5. 4 投信平均績效與排名 54
表 5. 5 各投信專長基金長期績效排名(前四家) 56
表 5. 6 績效與集中度變數敘述統計表 57
表 5. 7 基金效率值分位數區間平均值狀況 57
表 5. 8 受限制分位數迴歸變數敘述統計表 58
表 5. 9 各季效率值敘述統計表 59
表 5. 10自變數相關係數表 60
表 5. 11自變數相關係數表(續) 60
表 5. 12以產業集中度為集中度指標之估計結果 62
表 5. 13以產品集中度為集中度指標之估計結果 63
表 5. 14以集團集中度為集中度指標之估計結果 64
表 5. 15以個股集中度為集中度指標之估計結果 65
表 5. 16以股票持有家數為集中度指標之估計結果 66
表 5. 17集中度指標於各區間顯著性匯總表 69
表 5. 18以五種集中度指標同時估計之結果 71

圖目錄

圖1. 1 國內各類型基金規模成長比較圖 2
圖1. 2 研究架構圖 7
圖2. 1 SML線 13
圖2. 2 CML線 13
圖5. 1產業集中度(ICI)與效率值之係數關係圖 67
圖5. 2產品集中度(PCI)與效率值之係數關係圖 67
圖5. 3集團集中度(GCI)與效率值之係數關係圖 68
圖5. 4個股集中度(SCI)與效率值之係數關係圖 68
圖5. 5持股家數(Num)與效率值之係數關係圖 69

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