§ 瀏覽學位論文書目資料
  
系統識別號 U0002-2502200816274300
DOI 10.6846/TKU.2008.00878
論文名稱(中文) 原油價格變動對歐洲不動產投資信託市場之影響-以法國、比利時為例
論文名稱(英文) The Impact of Oil Price on European REITs Markets: Evidence from France and Belgium
第三語言論文名稱
校院名稱 淡江大學
系所名稱(中文) 財務金融學系碩士在職專班
系所名稱(英文) Department of Banking and Finance
外國學位學校名稱
外國學位學院名稱
外國學位研究所名稱
學年度 96
學期 1
出版年 97
研究生(中文) 吳慧瑩
研究生(英文) Hui-Ying Wu
學號 794490093
學位類別 碩士
語言別 繁體中文
第二語言別
口試日期 2007-12-29
論文頁數 54頁
口試委員 指導教授 - 邱建良
指導教授 - 陳玉瓏
委員 - 李命志
委員 - 蔡建雄
委員 - 陳若暉
關鍵字(中) 原油價格
不動產投資信託
雙變量GARCH模型
長短期公債預期利率
關鍵字(英) Oil Price
Real Estate Investment Trust
Bivariables GARCH Model
long-short term government bond interest rate
第三語言關鍵字
學科別分類
中文摘要
本文主要目的在於探討西德洲原油市場價格的波動,是否對於歐洲不動產投資信託(Real Estate Investment Trusts, REITs)報酬存在顯著的負面影響,以了解及提供市場決策者能有進一步的認知與參考資訊。在實證模型的選取上,本文採用一般正定雙變量GARCH模型進行估計,研究標的選取歐洲之法國與比利時作為實證對象,而樣本期間則涵蓋了2003年10月2日至2007年7月31日之日資料。在變數的選取上,除了考量其原油市場的波動外,於模型中分別引入三個月國庫券利率、十年期公債利率及兩國大盤股市報酬之變數予以探討,以分析其股債市與REITs報酬之間的關聯。此外,更進一步針對兩國長短期公債利率採用ARMA模型進行配適,以捕捉市場預期心理因素對REITs報酬的影響。
實證結果發現:1.在債市與股市的部份,比利時REITs報酬對長短期公債預期利率不具敏感性,而法國REITs報酬對長期公債預期利率具有負向之敏感性,顯示不同國家對於利率的敏感性並無一致性的結果;此外,兩國大盤股市報酬皆呈現出正向顯著的關係。2.在油價波動方面,兩國REITs報酬對於油價上漲,並無負向顯著的影響,隱含出現今油價高漲不斷的時代,投資人在進行歐洲權益市場投資時,納入REITs商品將可減低油價攀升所帶來的衝擊,達到分散風險的目的。3.比利時與法國REITs報酬存在顯著波動叢聚的現象,且兩國具有報酬波動互動的效果,顯示歐洲REITs市場報酬具有連動之情形。4.另一方面,比利時REITs的報酬受其法國前期REITs報酬的影響,但反之則不存在,表示市值規模較大之國家,其不動產市場的榮枯將影響市值規模較小的國家。
最後,希冀本文實證結果能提供市場投資人在進行歐洲不動產市場之投資決策時,能有更進一步的認知與分析資訊,以降低整體投資組合報酬的波動及其潛在的風險。
英文摘要
The purpose of this paper is to explore the fluctuation of crude oil pricing in west Texas and significant negative affect, if any, towards European Real Estate Investment Trusts, (REITs) to understand and offer the decision maker of this market with further cognizance and reference information. This paper will use the bi-variables GARCH model in conjunction with example of data from France and Belgium, dating from 2nd, October, 2003 to 31st July, 2003. Considered variables and analysis the relationship between stock/bond market and REITs include: The West Texas Cushing Oil spot price growth rate, long-short term government bond interest rate and stock market returns. Furthermore, matching long and short term government bond interest rate of the two countries utilizing the ARMA model will capture the expected interest rate from market practice as the psychological factor affect to REITs returns.
Examples in this research have proven that: 1.Belgium REITs return is insensitive to both long and short term government bond expected interest rate and the French REITs return is significantly sensitive to long term government bond expected interest rate obtains negative results, which means different countries may not obtain similar result to various interest rate fluctuations. Additionally, the returns of stock market in both nations appear significant positive results. 2.The fluctuation of petroleum prices, REITs returns of these two countries has no significant negative affect towards crude oil price uplifts.  This implies at this time in age, skyrocketing crude oil pricing, when investors invests in the European controlling interest market, the intake of REITs products may minimize the risk impact brought upon by the crude oil price undulation, to disperse the risk factor. 3. REITs returns of Belgium and France has significant volatility clustering characteristic, which results in correlating fluctuation effect of the REITs returns.  This reveals the European REITs market returns rate has chained effects. 4.On the other hand, the Belgium REITs’ return is affected by first quarter of French REITs return, but not the other way around.  This means, in a nation with larger scaled market capitalization, the prosperity of its real estate market will affect the nations with smaller market capitalization scale.
Lastly, I sincerely wish the findings in this paper may offer investors with further knowledge and analytical information when making real estate investment decisions toward the European market in hoping to avoid potential risk and minimize fluctuation of the integrated portfolio returns.
第三語言摘要
論文目次
目     錄
第一章  緒論	1
第一節  前言	1
第二節  研究動機及目的	3
第三節  研究架構	5
第二章 不動產投資信託市場介紹與相關文獻回顧	6
第一節  不動產證券化意義	6
第二節  各國不動產投資信託介紹	9
第三節  不動產投資信託相關文獻	12
第三章  研究方法	21
第一節  單根檢定	21
第二節  ARMA(p,q)模型	25
第三節  ARCH 模型	26
第四節  單變量GARCH模型	28
第五節  多變量GARCH模型	28
第六節  模型設定	32
第四章  實證結果與分析	34
第一節  資料來源及處理	34
第二節  基本統計量分析	35
第三節  ARIMA模型配適	40
第四節  單根檢定	41
第五節  ARCH檢定	42
第六節  GARCH模型的估計與檢定	43
第五章	結論與建議	48
第一節 結論	48
第二節 建議	49
參考文獻  50

表    次
【表1.1.1】全球不動產投資信託家數及市值比較圖	2
【表2.2.1】SIIC與SCPI比較彙整表	11
【表4.2.1】法國與比利時REIT報酬共變數\相關係數	37
【表4.2.2】比利時變數的簡單統計量	37
【表4.2.3】法國變數的簡單統計量	37
【表4.3.1】ARIMA(p,q)模型配適結果	40
【表4.4.1】法國與比利時各變數之單根檢定	41
【表4.5.1】ARCH 效果檢定	42
【表4.6.1】法國與比利時之雙變量GARCH(1, 1)估計結果	45

圖    次
【圖1.3.1】研究流程圖	5
【圖4.2.1】比利時REITs指數走勢圖	38
【圖4.2.2】法國REITs指數走勢圖	38
【圖4.2.3】西德州中級原油價格走勢圖	38
【圖4.2.4】兩國三個月期國庫券利率走勢圖	39
【圖4.2.5】兩國十年期公債利率走勢圖	39
【圖4.2.6】兩國股價指數走勢圖	39
【圖4.6.1】比利時REITs條件變異數 (conditional variance)	47
【圖4.6.2】兩國REITs共變異數	47
【圖4.6.3】法國REITs條件變異數(conditional variance)	47
參考文獻
一、中文部分	
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