本研究以Copula-GARCH方法建構一含原物料商品投資組合，資產內容包括：黃金、原油、棉花、股市和債市五大類，並於每類型資產選出代表性標的共計12項資產。採用GARCH(1,1)-t配適資產之邊際分配。在資產間關聯性部分，以Copula取代傳統線性相關係數，捕捉資產間關聯結構。最後根據CVaR，報酬率標準差最小化，Mean-Variance和CRRA效用極大化等決策準則計算權重建構投資組合。
研究結果顯示，以Copula-GARCH方法建構投資組合時，以過去半年歷史資料建立未來10天的投資組合績效最佳。當以CRRA效用函數決定權重時，在考量不同投資人風險趨避程度下，風險趨避程度越小，投資組合獲利越高，波動度亦越高。最後本研究以金融海嘯做為分界觀察不同時期資產配置的變化。發現金融海嘯前，投資以股市為重心。金融海嘯期間，資金轉進債市和黃金避險。金融海嘯後，資產配置較平均，其中棉花的比重大幅上升，黃金維持金融海嘯以來的高比重，反映近年來原物料市場亮麗的表現。

This paper applied Copula-GARCH methodology for asset allocation of a portfolio with commodities, including, gold, oil, cotton, stock, and bond. We used GARCH(1,1)-student- t to fit the marginal distribution. Instead of correlation, we applied Copula to capture the dependence structure between assets, and solved the optimal weight by minimizing CVaR, standard deviation, or maxing Mean-Variance, or CRRA utility function.
In this study, we found that it is optimal to invest in future 10 days based on the historical data of the past 126 days. We constructed portfolios for investors with different degree of risk aversion. The empirical results showed that the less risk aversive, the higher both portfolio performance and volatility is. Finally, we observed the change of weights between assets. The stock primarily constituted the portfolio before 2008. During the period of financial tsunami, the proportion of bond and gold grew up significantly. After 2009, commodities played an important role in portfolio.

目錄
第一章、緒論 1
第一節、研究背景及動機 1
第二節、研究目的 3
第二章、文獻回顧 4
第一節、投資組合理論 4
第二節、Copula之相關運用 4
第三節、原物料商品之相關研究 5
第三章、研究方法 8
第一節、Copula理論 8
第二節、多變量Copula模型 10
第三節、Copula-GARCH 11
第四節、決策準則 12
第五節、資產選取 13
第四章、實證分析 17
第一節、資料描述 17
第二節、投資組合效益分析-樣本期間選取 19
第五節、投資組合效益分析-t Copula 26
參考文獻 32

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