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研究生： 邱文輝
Chiu, Wen-Hui
論文名稱： 在控制資料探勘偏誤下探討社會責任共同基金之績效
Examining the performance of SRI mutual funds based on data-snooping biases free approach
指導教授： 顏盟峯
Yen, Meng-Feng
學位類別： 碩士
Master
系所名稱： 管理學院 - 財務金融研究所
Graduate Institute of Finance
論文出版年： 2010
畢業學年度： 98
語文別： 英文
論文頁數： 48
中文關鍵詞： 社會責任投資 、資料探勘偏誤 、假性推論 、橫斷面拔靴法
外文關鍵詞： SRI, data-snooping biases, spurious inference, the cross-sectional alpha bootstrap technique
相關次數： 點閱：141  下載：3 
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    • 近二十年來社會責任投資(Socially responsible investment, SRI)是個在共同基金市場中快速成長的領域。一般而言，過去的研究認為社會責任投資基金和一般基金之間並沒有任何績效上的差異，然而在過去風險調整基礎下所做的績效衡量，其統計推論在資料探勘偏誤(data-snooping biases)的影響下是不具可靠性的，因此本研究應用了由Kosowski 等人在2006年所發展的橫斷面拔靴法來檢驗社會責任投資基金和一般的共同基金在1990至2009年間是否有績效上的差異。事實上，本研究發現了資料探勘偏誤的確讓我們做出了假性推論(spurious inference)，另一方面也發現了社會責任投資基金和一般共同基金間的績效並無差異，兩者也沒有績效的持續性，甚至對兩類別基金而言，績效都顯著低於市場投組。

    Socially responsible investment (SRI) is a rapidly growing field in the mutual fund market for last two decades. In general, past research supports that there is no difference in performance between SRI and conventional funds. However, prior findings, on a risk-adjusted basis, are not reliable due to data-snooping biases. In this paper, I implement a bootstrap analysis in the cross section of alphas provided by Kosowski et al. (2006) to examine the performance in SRI and conventional funds and to compare their performance over the 1990 to 2009 period. In fact, my study uncovers that the data-snooping biases indeed lead us to make spurious inference. It is also found that there is no difference in fund performance between SRI and conventional funds and that performance persistence is inexistent for two groups. Furthermore, both SRI and conventional fund managers underperform the benchmark portfolio.

    I. Introduction 1 II. Literature Review 4 II.1. Performance Measure Approach 4 II.2. Performance Measure Using Bootstrap Method 6 II.3. Financial Performance of SRI Fund 8 III. Methodology 10 III.1. Data Collection Procedure 10 III.2. Research Method 15 III.2.1. The Factor Models 15 III.2.2. The Stationary Bootstrap 16 III.2.3. KTWW’s Cross-Sectional Alpha Bootstrap Technique 18 III.2.4. The Bootstrap Analysis of Performance Persistence 20 IV. Empirical results 23 IV.1. Bootstrap Tests of Cross Section of Fund Alphas 23 IV.2. Bootstrap Performance Persistence test 29 V. Conclusion 36 REFERENCES 37 APPENDIX 39

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