臺灣博碩士論文加值系統

在全球金融危機期間，美國房價下跌導致許多銀行和金融機構的重大危機，也引發了全球股票市場價格、商品價格和國際房地產市場價格的急劇下跌。由於不同資產之間的報酬率會隨著市場所承受的壓力產生不同的變化，探究不同資產與不動產之間的關係，在過去或現今都是重要的研究議題。本研究探討美國十個城市包括波士頓、芝加哥、丹佛、拉斯維加斯、洛杉磯、邁阿密、紐約、聖地牙哥、舊金山及華盛頓之不同資產對房價的影響，並利用Bianchi et al. (2017)所提出的隨機性轉變的Beta係數，與變異數之貝氏模型平均法，來觀察S&P/Case-Shiller房屋價格指數報酬與景氣同時指數、金融壓力指數、波動率指數、石油價格、黃金價格、不動產投資信託的關係；此研究方法較過去創新，且結果也較為準確。
分析後發現，房市異常報酬率在2005-2009年呈現明顯的下降，其中，下降最為明顯的前三個城市分別為洛杉磯、邁阿密及拉斯維加斯，此現象與當時的美國房地產市場泡沫破滅的時間一致。再來，景氣同時指數、金融壓力指數與不動產投資信託三個變數對房價的影響力會隨時間改變，且景氣同時指數與金融壓力指數兩個變數的解釋力又比不動產投資信託價格變數來的大。其中，拉斯維加斯的房市受景氣同時指數的影響最大，邁阿密受金融壓力指數影響最大。因此，景氣同時指數與金融壓力指數兩變數對於房價報酬的影響更顯重要，對於投資人在投資及風險分散也具有一定的參考價值。然而，可以觀察出大部分的城市之房市報酬受波動率指數、石油價格與黃金價格的波動較不明顯。另外，本研究發現不同資產對房價的影響會隨著時間改變之嶄新實證結果。

During the global financial crisis, the decline in the United States housing prices led to the distress of many banks and financial institutions. It also triggered a sharp decline in global stock market prices, commodity prices and international real estate market prices. Since the returns across different assets vary with the pressure embedded in the market, exploring the relationship across different assets has been an important research issue. This study explores the impact of various financial indexes on S&P/ Case-Shiller housing prices in the 10 main cities of the United States, including Boston, Chicago, Denver, Las Vegas, Los Angeles, Miami, New York, San Diego, San Francisco, and Washington, utilizing Bayesian model averaging method proposed by Bianchi et al. (2017). The innovative model is featured by the time-varying beta coefficient which enables us to observe the dynamic relationships across house prices and the coincident index, the financial stress index, the volatility index, oil prices, Gold prices, and Real Estate Investment Trusts (REITs).
The findings suggest that there was a substantial decline in housing abnormal returns from 2005 to 2009. The top three cities with the most significant decline are Los Angeles, Miami and Las Vegas, and the period coincides with the burst of the US housing market bubble. The impacts of the three variables, including the coincident index, the financial stress index and the REIT price index, tend to change over time. The explanatory power of the coincident index and financial stress index is larger than that of the REIT price index. Among the 10 main cites, the impact of the coincidence index in Las Vegas is the strongest, and that of the financial stress index in Miami is the most substantial. Therefore, the two variables of the coincident index and the financial stress index play important roles in driving housing prices, and they are informative for investment decision-making and risk diversification. However, the housing prices in most cities are marginally affected by the volatility index, oil prices, and gold prices. The study provides novel evidence for time-varying impacts of financial indexes on indexed house prices.

謝詞 I
中文摘要 II
ABSTRACT III
目　錄 IV
圖　次 VI
表　次 XII
第一章　緒論 1
第一節　研究背景 1
第二節　研究動機與目的 1
第三節　研究流程 2
第二章　文獻探討 3
第一節 房價指數相關文獻 3
第二節 解釋變數之相關文獻探討 4
第三章　研究方法 9
第一節 研究資料 9
第二節 研究模型 10
第四章　實證結果 13
第一節 敘述統計 13
第二節 2004~2018年間房市報酬率 16
第三節 房價報酬率之解釋變數影響力分析 17
第五章　研究結論與建議 21
第一節　管理意涵 21
第二節　未來研究與方向 22
參考文獻 23
附錄一　各解釋變數對城市影響動態圖 27
附錄二 各解釋變數之成長率 39
著作權聲明 41

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