本研究藉由觀察不動產與其他資產之關聯性，以台灣投資人的角度出發，試圖為台灣投資人提供投資組合建構之參考。首先遴選台灣投資人可接觸度較高之股票、利率、美元、黃金，並加入影響經濟甚巨的原油，以1974年至2012年之長期資料檢視這五項資產與不動產之關聯結構，資料頻率則為季資料。
　　考慮到資產報酬率多具有波動結構不對稱與時間序列等特性，因此本研究採用GJR-GARCH-skew t作為各資產報酬邊際分配之模型。再者，傳統多變數機率分配如多元常態分配在使用上有結構對稱、邊際分配必須為常態分配等諸多限制，故以copula模型連結各資產。而再考量到相關係數可能因時而異，故除了靜態copula模型外，亦採用動態copula模型。最後，本研究試以copula vine聯結六項資產為一機率分配，藉以觀察各資產間的關聯。
　　本研究實證結果顯示，不動產在六項資產中明顯具有高報酬率、低波動性，且與其他資產之線性相關係數均不高。而不論在靜態copula或動態copula的估計結果裡，不動產均與其他資產無長期且明顯的相關。最後，copula vine的實證結果也顯示不動產並非各資產間相互影響的橋樑。由上述結果可知，不動產具有與其他任何資產關聯性均低的性質，加上穩定的高報酬率，顯見在投資組合中加入不動產對分散風險與提升報酬應具有良好的效果。另外，在動態copula分析中，本研究亦觀察到房地產與其他資產的關聯會受國內中央銀行調控方向、中台外交事件、中東情勢、國際金融危機四大因素影響。故本國投資人應按照事件性質略為調整其投資組合。

This study investigates whether we can improve the portfolio performance by adding real estate when constructing a portfolio from the perspective of Taiwanese investors by observing the relationship between real estate and other assets. In order to focus on Taiwanese investors, this study selects five assets which are easily accessible to them, including stock, interest rate, US dollar, gold, and especially oil, which has a significant influence to economy. And the seasonal data from 1974 to 2012 is involved in this paper.
　　Considering the return of assets, this study takes GJR-GARCH-skew t as marginal distribution of each asset. Traditional multivariate probability distribution, such as normal distribution, has several constraints, including the symmetric structure and the normal marginal distribution, and so on. However, the assumptions are different from the reality. Copula, which allows asymmetric structure involve in joint distribution, and is flexible in choosing marginal distribution, is a method frequently used to solve these problems in recent years. Furthermore, considering that correlation coefficient is fluctuant with time, this study uses both static copula and dynamic copula. Finally, we use copula-vine to simply connect all variants to observe the relationship between assets.
　　Empirical Results show that real estate not only has significantly higher return and lower variance, but also has low correlation coefficient with other assets. No matter in static copula model or dynamic copula model, there is no significant evidence reveals that real estate is related to other assets in the long run. In copula-vine model, the result shows that real estate is not bridge between other assets. By the foregoing, real estate features high and stable return, relatively low variance and low correlation with other assets. Therefore, if investors add the real estates in their portfolios, it can enhance the performance of their portfolios. Besides, in dynamic copula analysis, this study finds that the correlation between real estates and other assets mainly influenced by four types of events, including policies of Central Bank of the Republic of China, the diplomatic events between Taiwan and mainland China, the condition of the Middle East and international financial crisis. As a result, this study suggests that domestic investors should adjust their portfolio by these events.

論文審定書 i
致謝辭 ii
摘要 iii
Abstract iv
目錄 v
圖目錄 vii
表目錄 viii
第一章 緒論 1
　第一節 研究背景 1
　第二節 研究目的 4
　第三節 研究設計 5
　第四節 研究架構 7
第二章 文獻探討 8
　第一節 不動產與其他資產之關聯 8
　第二節 投資組合 10
　第三節 Copula 12
　第四節 Copula vine 14
第三章 研究方法 15
　第一節 邊際分配模型 16
　第二節 Copula 18
　第三節 Copula vine 21
　第四節 參數估計 25
第四章 實證結果 28
　第一節 資料說明 28
　第二節 敘述統計量 30
　第三節 相關性分析 34
　第四節 copula　 35
　第五節 copula vine 43
第五章 研究結論與建議 46
　第一節 研究結論 46
　第二節 研究限制與建議 48
參考文獻 49
　國內文獻 49
　國外文獻 49
附錄 53

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