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中文論文名稱 應用Copula-ARMAX-EGARCH模型探討大中華地區不動產與總體經濟間的傳染效應
英文論文名稱 Contagion effects between real estate and macroeconomic factors across Great China Area based on Copula-ARMAX-EGARCH model
校院名稱 淡江大學
系所名稱(中) 財務金融學系碩士班
系所名稱(英) Department of Banking and Finance
學年度 99
學期 2
出版年 100
研究生中文姓名 陳詩佳
研究生英文姓名 Shih-Chia Chen
學號 698530051
學位類別 碩士
語文別 英文
口試日期 2011-05-08
論文頁數 78頁
口試委員 指導教授-李沃牆
委員-邱建良
委員-林維垣
委員-張揖平
中文關鍵字 ARMAX-EGARCH  Copula  Tail dependence  Contagion effect 
英文關鍵字 ARMAX-EGARCH  Copula  Tail dependence  Contagion effect 
學科別分類 學科別社會科學商學
中文摘要 本文研究之目的是採用文獻上較罕見的ARMAX-EGARCH配適動態分配房價指數報酬率,因其考量外生變數,故配適度較佳,並藉由Copula-ARMAX-EGARCH推估大中華地區房市傳染效應之嚴重性。儘管Copula能捕捉任兩區全方面不動產報酬波動的相關性,但當極端事件發生時,Tail dependence 才能有效地掌握尾部相關切確值,有鑑於美國次級房貸對全球經濟的影響甚鉅,了解此區彼此房市間的傳染效應為當務之急。
實證結果發現大中華地區房市報酬率確實受其本身不同的總體變數所影響,就Copula而言,台灣對香港及台灣對中國皆採用較敏感的Student-T,另外,Tail dependence的Gumbel證實前者在房市繁榮時有相關性,透過橢圓及阿基米德Copula家族估算,此區房市傳染效應皆小於19%,初步推估此區房市有風險分散的效益。
英文摘要 The purpose of this paper fits dynamics distribution housing indices returns estimates the severity of contagion effect across Great China Area real estate markets based on Copula-ARMAX-EGARCH. Although the model is rare in literatures, it provides a better fit due to exogenous variables. Even though Copula could comprehensively capture the correlation of any two real estate volatilities of these areas, it fails once an extreme event outbreaks, but tail dependence could exactly estimate the bilateral degree of correlation in that case. In view of the great influence of U.S. subprime mortgage to global economy, understanding the contagion effects between any two of these areas property markets is urgent.
論文目次 Content
Abstract: III
Content IV
Table Content V
Figure Content VI
Chapter 1 Introduction 1
1.1 Background and motivation 1
1.2 Objective 6
1.3 Contribution to the literature 6
1.4 Thesis overview 7
Chapter 2 Theory and Literature 9
2.1 Macroeconomic and real estate market 9
2.2 Literature review 11
Chapter 3 Methodology 22
3.1 ARMAX-EGARCH model 22
3.1.1 ARMAX (m,n) model 23
3.1.2 EGARCH (p,q) model 26
3.1.3 ARMAX(m,d,n)-EGARCH (p,q) model 28
3.2 Copula-ARMAX-EGARCH model 29
3.2.1 Copula model 29
3.2.2 COPULA-ARMAX-EGARCH model 37
3.3 Tail dependence 38
3.4 The conditional probability of contagion effect 39
Chapter 4 Empirical Design and Results Analysis 41
4.1 Data description 41
4.2 Estimation 44
4.2.1 ARMAX(1,0,7)-EGARCH(1,1) model 45
4.2.2 Copula-ARMAX(1,0,7)-EGARCH(1,1) model 51
4.2.3 Tail dependence 55
4.2.4 The conditional probability of contagion effect 57
Chapter 5 Conclusion and Suggestion 64
Reference 67

Table Content
Table 1: Integration of macroeconomic factors for the relevant literatures 13
Table 2: Elliptical copulas’ details and Kendall tau 34
Table 3: Archimedean copulas’ details and Kendall tau 36
Table 4: Tail dependence of three copulas 39
Table 5: Great China Area real estate indices sources 41
Table 6: Great China Area’s real estate indices statistics 42
Table 7: The parametric estimation results of ARMAX(1,0,7) - EGARCH(1,1) 50
Table 8: The Kendall’s tau of copula functions 52
Table 9: Tail dependence of Student-T, Clayton and Gumbel Copula 55
Table 10: Conditional probability of contagion effect for elliptical copulas 60
Table 11: The investment priorities for Great China Area housing markets 61
Table 12: Conditional probability of contagion effect for Clayton & Gumbel Copulas 62
Table 13: Conditional probability of contagion effect for Frank Copula 63

Figure Content
Figure 1: Asian map 5
Figure 2: The flow chart of this thesis 8
Figure 2: Great China Area Real Estate Indices 42
Figure 3: The frequency distribution of the returns of three real estate indices 43
Figure 4: QQ plot for Great China Area indices returns 43
Figure 5: Foreign Direct investment in Taiwan real estate 46
Figure 6: Bilaterally marginal distribution density function of elliptical copulas 53
Figure 7: Bilaterally marginal distribution density function of Archimedean Copulas 56

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