本篇論文旨在研究美國的不動產與金融市場之間的關聯結構，金融市場包含
了股票市場、債券市場以及外匯市場，資料期間約從 1975 年至 2010 年。模型將
採用三種動態 copula 來衡量其關聯性，包括 Gaussian, Gumbel 以及 Clayton
copula，其中 Gumbel 以及 Clayton 分別針對資產市場與房地產市場之間的左、
右尾相關做分析。Copula 模型裡的參數將可以分別對房地產指數(HPI 或 NEREIF)
和三個金融市場分析關聯性。而本文將依不同的指數而對房地產進行兩階段的分
析，第一階段為不同美國地區的分析(HPI)，第二階段為不同房地產類型的分析
(NCREIF)。本文的主要研究目的除了研究美國房地產與金融市場的相關性，亦
有從中分析當金融危機爆發後的關聯結構是否發生改變。
實證結果指出，不動產與股票市場具有正相關，而關聯性會因為金融危機爆
發後有著巨幅的波動，這波動是關聯性提高還是降低需要看這些危機事件的性質，
舉例來說，2000 年的網路泡沫化就與 2008 年的次級房貸風暴在本質上就不同，
所以關聯性的波動方向也不同。至於債券利率與房地產的關聯性大致與股市相同，
正相關且危機出現時波動性會大增。而房地產與外匯的關係為負，但也意味著美
元的強弱與房地產指數的高低為正相關，且一樣在危機爆發時有較大的波動性。
整體來說，不同地區或是不同類型之間差異不大，同為正相關且大多同時具有右
尾以及左尾相關，而少部分市場存在單一右尾或左尾相關。不過因為指數的特性
不同，因此投資人可以聚焦於市場間的風險分散，而非將焦點放在投資何種區位
或是類型的不動產。

This paper studies the dependence structure between the real estate and financial
markets in the United States from roughly 1975 to 2010, including the stock, bond
and foreign exchange markets. This analysis uses dynamic copulas, including the
Gaussian, Gumbel and Clayton copula. The Gumbel and Clayton copulas are used to
separately capture the tail dependence of data. The dependence between the property
indices (HPI and NCREIF) and the three financial markets is analyzed using the
parameters of the copula. The property indices are divided in two different ways: by
different regions and by different types of real estate. Although we study the
dependence between the real estate and the financial markets in the U.S., the main
objective of this paper is to analyze the change in the dependence structure when
financial disasters occur.
This study indicates that the real estate and the stock markets were positively related
during this time period, and this dependence drove extreme movement when financial
crises occurred. This dependence differed depending on the type of financial crisis,
such as the Internet bubble crisis or the financial crisis in 2008. The dependence
between the real estate and bond markets was also positively related, and extreme
movement also occurred during financial crises. As for the dependence between the
real estate and foreign exchange markets, although the results shows that dependence
decreased when financial crises occurred, this is because the value of U.S. dollars are
opposite to those of the index, and the left tail dependence exists as previous result.
When looking at different regions or types of property, the differences in dependence
structure were not obvious, although they were positively related. Both right and left
tail dependences existed for most regions and property types, although some regions
or types showed either right or left tail dependences alone. Therefore, investors should
focus on the relationship between different markets, not on the region or type of real
estate.

摘要 i
Abstract ii
List of Figures iv
List of Tables v
Chapter 1 Introduction 1
Chapter 2 Literature Review 4
2.1 The relationship between the real estate and financial markets 4
2.2 Related literatures of Copula 6
2.3 Summary 7
Chapter 3 Econometric Methodology 8
3.1 Time series model 8
3.2 The parameters of copula 8
3.3 Time-varying parameters 9
Chapter 4 Data and Empirical Results 12
4.1 Data and descriptive statistics 12
4.2 Linear Correlation 14
4.3 Dynamic copulas 15
4.4 Nonlinear dependence structure 19
4.4.1 The dependence between property indices and the S&P 500 19
4.4.2 The dependence between property indices and the 10-year government bond 27
4.4.3 The dependence between property indices and the USDX 34
Chapter 5 Conclusion and Implication 42
5.1 Conclusion 42
5.2 Implication and Suggestion 43
Reference 44

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