本文應用Markowitz(1952) 的平均數-變異數模型(Mean-Variance Model)來探討最適資產的配適。實證上選取台灣五十指數成分股為投資組合標的，經由動態的移動視窗法，以2008年9月5日至2009年8月28日共51筆週報酬資料做為第一期樣本資料，利用動態的方式對不同的模型去估計投資組合成分股下一期平均數、變異數和共變異數，再藉由平均數-變異數模型，導出下一期所應投入的投資組合最適權重。根據這些權重來預測2009年9月4日至2010年8月27日所應該要配適的最佳投資組合。透過不同的績效指標進行評估，發現利用DCC-GARCH模型去估計參數，相較於傳統平均數-變異數模型以歷史資料評估不但較能正確反映市場走勢，也有較佳的預測能力及投資績效。

This paper use the Mean-Variance Model of Markowitz(1952) to discuss the allocation of the optimal assets. We use the component stocks of Taiwan 50 Index for the underlying of the portfolio. Through the dynamic moving window estimation, we use the weekly return from 2008/9/5 to 2009/8/28 for the first sample data. Estimate the portfolio’s mean, variance and the covariance of the next period of different kinds of model by dynamic method, then using the Mean-Variance Model to derive the optimal weight of the portfolio. We use this weights to forecast the allocation of the optimal assets from 2008/9/4 to 2010/8/27. This paper found that through the estimation of the different performance index, compare to the Mean-Variance Model, DCC-GARCH model is not only more accurate to reflect the market trend but also has better forecast ability and investment performance.

目 錄
第一章	緒論	1
第一節	研究動機	1
第二節	研究目的	4
第三節	研究架構與流程	5
第二章	理論基礎與相關文獻回顧	6
第一節	資產配置	6
第二節	資產多角化(DIVERSIFICATION)	8
第三節	MARKOWITZ 投資組合理論相關文獻	8
第四節	波動性模型相關文獻	10
第三章	研究方法	13
第一節	MARKOWITZ 投資組合模型	13
第二節	GARCH相關特性與模型	16
第三節	績效評估	25
第四節	研究步驟	29
第四章	實證研究	30
第一節	研究資料與設定	30
第二節	成分股敘述統計分析	34
第三節	模型結果分析	38
第五章	結論與建議	52
第一節	結論	52
第二節	建議	54
參考文獻	55
表目錄
表4.1 台灣五十前二十名權重之股票代碼與權重	30
表4.2 台灣五十二十支成分股敘述統計數據	35
表4.3 三種動態模型投資組合內成分股的出現的次數	40
表4.3.1 DCC-GARCH(1,1) 模型最適權重	41
表4.3.2 CCC-GARCH(1,1) 模型最適權重	43
表4.3.3 HISTORICAL模型最適權重	45
表4.4 投資組合實際報酬敘述統計	48
表4.5 四種模型的績效指標評估表	50
表4.6 不同模型成對T檢定表	51









圖目錄
圖1 效率前緣	13
圖2 資本市場線與效率前緣	14
圖4.1 台灣五十指數和加權指數週收盤價	31
圖4.2.1 台灣五十二十支成分股次數分配圖(1)	36
圖4.2.2 台灣五十二十支成分股次數分配圖(2)	37
圖4.3 預測2009/01/04的最適投資組合	39
圖4.4 不同模型的投資組合實際報酬圖	48

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