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研究生:陳俊成
研究生(外文):Chun-Cheng Chen
論文名稱:主動型基金經理人操作績效的厚尾統計管制圖
論文名稱(外文):Heavy-tail statistical monitoring charts of the active managers'' performance
指導教授:郭美惠郭美惠引用關係
指導教授(外文):Mei-Hui Guo
學位類別:碩士
校院名稱:國立中山大學
系所名稱:應用數學系研究所
學門:數學及統計學門
學類:數學學類
論文種類:學術論文
論文出版年:2006
畢業學年度:94
語文別:中文
論文頁數:46
中文關鍵詞:拒絕-接受抽樣法混合常態分佈廣義誤差分佈厚尾分布CUSUM管制圖資訊比值基金績效評估
外文關鍵詞:Generalized error distributionInformation RatioMixture Normal distributionCUSUM control chartfat tailperformance measurementAcceptance-Rejection sampling method
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許多評估主動基金經理人操作績效的方法,須經一段時間之後才得以建立;然而大部分的投資人,總是希望在經理人的操作出現問題時能儘快察覺,以便適時地調整投資組合的目標和內容,來降低投資風險;Yashchin,Thomas與David (1997),提供一個統計品管(SQC)的方式來監控主動基金經理人的績效;據此建時表現。
然而在許多基金中,資訊比值常具有厚尾分布的特性;由於分佈是建立IR管制圖的重要假設,因此針對此問題,考慮了混合常態機率分佈、廣義誤差機率分佈兩種厚尾分佈來配適資訊比值;進一步,在較佳的模型配適下,重新建立對應的管制圖。利用模擬及實証的結果觀察所建立的管制圖;確實更能靈敏地察覺主動基金經理人績效的變動。
Many performance measurement algorithms can only evaluate measure active managers'' performance after a period of operating time. However, most investors are interested in monitoring the active managers'' performances at any time, especially, when the performance is going down. So that the investors can adjust the targets and contents of their portfolios to reduce their risks. Yashchin,Thomas and David (1997) proposed to use a statistical quality control (SQC) procedure to monitor active managers'' performances. In particular, they established the IR (Information Ratio) control charts under normality assumption to monitor the dynamic performances of active managers.
However, the distributions of IR statistic usually possess fat tail property. Since the underlying distribution of IR is an important hypothesis in building up the control chart, we consider the heavy tail distributions, such as mixture normal and generalized error distribution to fit the IR data. Based on the fitted distribution, the IR control charts are rebuilt. By simulations and empirical studies, the remedial control charts are found to detect the shifts of active managers'' performances more sensitively.
第一章 緒論 1

第二章 文獻探討 3
2.1資訊比值在基金績效評估上的意義........................ 3
2.2利用CUSUM的統計方法監控資訊比值的表現................. 5

第三章 混合常態與廣義誤差分佈 8
3.1 混合常態分佈及參數估計............................... 8
3.2 廣義誤差分佈及參數估計.............................. 9
3.3 廣義誤差分佈的CUSUM管制圖........................... 11
3.3.1 廣義誤差分佈的CUSUM統計量LN(G)................ 11
3.3.2 LN(G) CUSUM管制圖的門檻值及ARL值.............. 12
3.3.3 建立LN(G) CUSUM管制圖的實例說明及比較......... 13

第四章 資料分析與實証 17
4.1國內基金資訊比值的資料分析.......................... 17
4.2國內基金資訊比值的厚尾分佈配適實例.................. 18
4.3在GED與Normal假設下的CUSUM管制圖.................... 18
第五章 結論與建議 20
參考文獻 21
附錄 23
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Yashchin, E., Thomas, K. P., and David, M. S. (1997). ''Monitoring Active Portfolios Using Statistical Process Control.'' In Computational Approaches to Economic Problems. edited by Hans A., Berc, Rustem., and Andrew W., eds. Dordrecht, Netherlands: Kluwer Academic publishers.
Yashchin, E., Thomas, K. P., and David, M. S. (2003). ''Using Statistical Process Control to Monitor Active Managers.'' Journal of Portfolio management. 86-94.
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