Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/23531
標題: 基金相對績效與絕對績效之實證研究
An Empirical Study on the Performance Measurement of Mutual Funds in Taiwan
作者: 曾祥彥
Tseng, Hsiang Yen
關鍵字: Dtata envelopment analysis
資料包絡分析法
mutual fund performance
共同基金績效評估
相對績效
絕對績效
出版社: 財務金融系所
引用: 一、 中文部分 1. 末吉俊幸,「經營效分析法DEA」,2006年,鼎茂圖書,初版。 2. 林美菁(2000),利用融入參考點之資料包絡分析模式評估共同基金之相對投資績效,國立中央大學企業管理研究所碩士論文。 3. 陳哲瑜(2003),風險值在共同基金績效評估上之應用,國立中正大學企業管理研究所碩士論文。 4. 孫遜,「資料包絡分析法理論與應用」,2004年,揚智文化,五南,初版。 5. 張有若(2002),全球共同基金群組風險與績效評估,中原大學企業管理學系碩士學院論文。 6. 楊智傑(2007),平衡型基金績效評估研究-DEA之應用,長榮大學經營管理研究所碩士論文。 7. 廖含珮(2002),台灣共同基金績效之分析-資料包絡分析法之應用,中國文化大學經濟學系研究所碩士論文。 8. 蔡俊生(2004),投資組合之風險值衡量,世新大學管理學院財務金融學系碩士學位論文。 9. 薄喬萍,「績效評估之資料包絡分析法」,2005年,初版。 10. 顏月珠,「實用無母數統方法企管、醫療、環境及社會科學研究適用」1986年,陳昭明,初版。 二、 英文部份 1. Ang JS, Chua JH (1979)Composite measures for the evaluation of investment performance. Journal of Financial and Quantitative Analysis 14, 361-384. 2. Banker RD, Charnes A, Cooper WW (1984) Some models for estimating technical and scale efficiencies in data envelopment analysis. Manage Sci 30: 1078-1092. 3. Basso, A., Funari, S (2001) A data envelopment analysis approach to measure the mutual fund performance. European Journal of Operational Research 135, 17-32. 4. Basso, A., Funari S (2002) A generalized performance attribution technique for mutual funds. Working Paper n. 01. 08, GRETA. 5. Charnes, A., Cooper, W.W., Rhodes, E (1978) Measuring the efficiency of decision making units. European Journal of Operational Research 3,339. 6. Chen, Z., Lin R (2006) Mutual fund performance evaluation using data envelopment analysis with new risk measures OR Spectrum28:375-398. 7. Jensen, M.C (1968) The performance of mutual funds in the period 1945-1964. Journal of Finance 23,389-416.43 8. McMullen PR, Strong RA (1998) Selection of mutual fund using data envelopment analysis. J Bus Econ Stud 4:1-12. 9. Morey, M.R., Morey R.C (1999) Mutual fund performance appraisals: a multi-horizon perspective with endogenous benchmarking. Omega 27, 241-258. 10. Murthi, B.P.S., Choi, Y.K., Desai, P (1997) Efficiency of mutual funds and portfolio performance measurement: A non-parametric approach. European Journal of Operational Research 98, 408-418. 11. Pastor J (1996) Translation invariance in data envelopment analysis: a generalization. Annals of Operations Research 66:93-102. 12. Sharpe, W.F (1996). Mutual fund performance. Journal of Business 34, 119-138. 13. Treynor, J.L (1965) How to rate management of investment funds. Harvard Business Review 43, 63-75.
摘要: The performance indexes of mutual funds have been developed for more than 40 years since Treynor's index in 1965. Traditional indexes usually focus on the relationship between single risk variable and excess return only. The DEA indexes consider multiple inputs and multiple outputs compare to traditional indexes. However, DEA indexes can only measure relative performance rather than the absolute performance measurement as like traditional indexes can do. In this paper, we compared the relative and the absolute performance measurement results of mutual funds in Taiwan. We compared performance results using four traditional indexes (Sharpe, Treynor, reward to half variance, Jensen) and four DEA indexes (DPEI, IDEA_1, IDEA_g, IDEA_g with VaR). The main differences among four DEA indexes are subject to different risk variable and take into account of traditional indexes in output variables or not. DPEI index using the annual standard deviation as risk variable, IDEA_1 index using both β coefficient and root of the lower half variance and IDEA_g considered traditional indexes in their risk measurement. Finally, ”IDEA_g with VaR” considered Value at Risk (VaR) as risk variable . The main empirical results are concluded as follows: 1. By ranking the performance results of traditional versus DEA indexes separately, we found their results are not consistent between absolute and relative performance measurement. 2. We found the results keep consistently among traditional indexes and among DEA indexes. 3. We also found the more variables in the DEA model, the more efficient it will be. However, when variables number of DEA model exceed half of DMU numbers, the DEA indexes will became inaccurate. 4. Finally, we found there exists high correlation coefficient among four DEA indexes. It means that more variables in the DEA model is not necessary in performance measurement of mutual funds.
基金績效指標從1965年的Treynor指標發展至今已有超過40年的歷史,從早期單純討論單一風險與超額報酬關係的傳統指標,發展成考慮多個產出與投入變數的DEA指標,雖然DEA指標較傳統指標考慮較多的變數,但是DEA指標只能探討相對績效,無法像傳統指標可以討論到絕對績效。 本文探討究竟相對績效與絕對績效評估基金績效有何差異,而一般投資大眾該選擇何種指標評估績效,針對傳統指標與DEA指標對基金績效評估,比較四個傳統指標(Sharpe、Treynor、reward to half variance、Jensen)與四個DEA指標(DPEI、IDEA_1、IDEA_g、加入VaR的IDEA_g)的實證結果,四個DEA指標最主要的差異在於風險變數的不同與是否在產出變數加入傳統指標,DPEI只有使用年化標準差做為風險變數,IDEA_1則加入了衡量系統風險的β值與衡量下方風險的較低半變異數平方根,而IDEA_g指標則較IDEA_1指標在產出變數中多了傳統指標,加入VaR的IDEA_g指標則在風險變數中多考慮了近年流行的VaR。 本文主要研究目的為探討考慮較多變數的DEA模型是否會使評估基金績效更加穩定與精準,實證結果如下: 一、 分別以DEA指標與傳統指標衡量對基金的績效作排序,結果顯著的不同, 顯示絕對績效與相對績效指標在台灣的基金市場上並不一致。 二、 傳統指標與傳統指標間具有高度相關性及一致性;相對績效指標(DEA)間也具有高度相關性與一致性,但DEA指標與傳統指標間則不具相關性及一致性。 三、 當DEA模式中包含的變數較多時,其有效率的單位會增加,若DEA的變數超過DMU個數的一半時,將會使得DEA指標的正確性受到質疑,好的DEA指標其DMU與變數的數量要適當。 四、 DEA指標間的高度相關,表示不需納入過多的變數,某些變數與變數之間存在高度的相關性。
URI: http://hdl.handle.net/11455/23531
其他識別: U0005-2406200822042000
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-2406200822042000
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