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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 荷世平 | |
dc.contributor.author | Hsi-En Chou | en |
dc.contributor.author | 周熙恩 | zh_TW |
dc.date.accessioned | 2021-06-13T04:22:06Z | - |
dc.date.available | 2013-08-03 | |
dc.date.copyright | 2011-08-03 | |
dc.date.issued | 2011 | |
dc.date.submitted | 2011-07-27 | |
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Zhang (2005), “Optimal Consumption and Portfolio Choices with Risky Housing and Borrowing Constraints.” Review of Financial Studies, 18, 197–239. 38. 葛萊姆.特納,「房子惹的禍:金融海嘯的起因、分析、終結」,繁星多媒體,2009.07. 39. 吳德進與李國柱,「房地產泡沫:理論.預警與治理」,社會科學文獻出版社,2007.10. 40. 蔡曜如(民92),「我國房地產市場之發展、影響暨政府因應對策」,中央銀行季刊,第二十五卷第四期,十二月,31-64頁。 41. 簡智崇(民97),「房價能否預測股票報酬?」,中央研究院經濟研究所,36:1(2008),89-139頁 42. 主計處(民99),「國富統計報告」,行政院主計處,八月。 43. 花敬群(民90),「自有率、空屋數量與住宅市場調整」,住宅學報,第十卷第二期,八月,127-137頁。 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/33018 | - |
dc.description.abstract | 次貸風暴時因房市泡沫化而延伸至經濟與股票市場的崩跌,造成了嚴重性的影響,故本研究想分析災難下房市經濟與股市間的相互關係,理解股市資產的波動是否會受到房市災難與經濟災難資訊影響。其次藉由考量災難資訊的定價模型,實證房地產市場崩跌事件能夠解釋股票行為多少程度,並與經濟災難資訊做比較。本研究應用較為客觀的數值方法(Bry-Boschan方法與Helbling and Terrones方法),來認定二十個已開發國家中的收縮期前1/4為災難。
災難分析結果呈現在含有房市災難或經濟災難的環境下,股票同期為負報酬的機率高達九成以上,且股票市場同時發生災難的機率也有五成左右,平均跌幅在-20%左右,顯示在災難環境中股票報酬是有明顯反應災難的情形。而房市與經濟災難間其波動對彼此皆有影響,當一方發生災難時,另一方發生災難的機率接近一半,顯示兩種災難可能伴隨一同發生。 其次檢驗考量災難資訊下的模型是否能解釋CCAPM中「股票溢酬之謎(Equity Premium Puzzle)」所提出模型解釋力不足6.18%股票風險溢酬值的部分。實證結果在考量了災難資訊下的模型相較於Lucas發展的傳統模型能更進一步解釋此溢酬問題,應用經濟災難資訊中解釋了6.83%的風險溢酬值,而考量了房市災難資訊下則能解釋3.39%風險溢酬值。這顯示了考量災難資訊後能夠使模型的解釋能力更好,且經濟災難資訊可以解釋大部分為何投資人們要求較高的風險報酬,房市上的災難考量則可補充經濟面所遺漏的部分災難資訊。兩種災難同時考量下,其合理的股票風險溢酬值為7.5%,可做為投資人在多考量經濟與房市災難影響下,所提出合理的風險報酬。 | zh_TW |
dc.description.abstract | Subprime Mortgage Crisis due to the housing market bubble which lead to economic recession and the stock market crash, causing the severity of impact. Therefore, this study is to analyze in the disasters, the relationship between the housing market, economy, and the stock market. To understand the changes in stock market assets, whether will be affected by the housing market and economic disaster information. Second, consider the disasters information to the asset pricing model to test the disaster events in real estate market, to explain how much of the stock investor behavior, and compare information with economic disaster. The study use a more objective numerical methods (Bry-Boschan methods and Helbling and Terrones methods) to identify twenty developed countries which the top 1/4 ranking of the contractions are disasters.
The study results show that in the hosuing market disaster or economic disaster environment, the stock have negative returns over 90%, and the shock market have the chances of disaster are about 50%, the average decrease of -20%, which appears the disaster situation is clearly reflected in the stock returns in the disaster environment. On the other hand, between the housing market and economic disaster are influenced by the fluctuation of each other. When one disaster, the other nearly half of the probability of a disaster, shows that the two may be accompanied with a disaster occur. Test the model under consideration of disaster information, whether the CCAPM can explain “Equity Premium Puzzle” proposed model to estimate the value of less than 6.18% equity risk premium value. Empirical results in the consideration of disaster information model compares to the traditional model of Lucas can further explain this premium issue. Information in the application of economic disasters explain 6.83% of the risk premium value, and consider the housing market disasters information is able to explain the 3.39% risk premium value. This shows that, after consideration of disaster information to make the model better describes the phenomenon of risk return, and economic disaster information can explain why most stock investors require higher risk premiums, and the housing market disaster information can supplement the missing part of the economic side of the disaster information. Two kinds of disaster at the same time considerations, the reasonable value of the equity risk premium of 7.5% can be considered for stock investors more information about the disaster effects, proposed a reasonable risk premium. | en |
dc.description.provenance | Made available in DSpace on 2021-06-13T04:22:06Z (GMT). No. of bitstreams: 1 ntu-100-R95521703-1.pdf: 5295480 bytes, checksum: bfbc7ce3a32c7b38f141847d566b55bb (MD5) Previous issue date: 2011 | en |
dc.description.tableofcontents | 論文口試委員審定書 I
致謝 II 中文摘要 III Abstract IV 目錄 VI 圖目錄 VIII 表目錄 IX 第一章 緒論 1 1.1 研究動機與目的 1 1.2 研究流程 4 第二章 文獻回顧 5 2.1 歷史上的泡沫 5 2.2 資產定價理論 6 2.3 災難概念的定價模型 7 2.4 罕見災難的認定 8 第三章 研究方法 10 3.1 實證流程 10 3.2 認定災難 11 3.3 考量災難資訊的資產定價模型 15 3.4 參數設定 20 第四章 實證成果與分析 21 4.1 資料描述 21 4.2 災難統計分析 25 4.3 不同市場間的下跌條件機率關係 34 4.4 模型參數值探討 47 4.5 風險溢酬於房市災難下與經濟災難下之探討 52 4.6 敏感度分析 59 第五章 結論與建議 61 5.1 結論 61 5.2 後續研究與建議 63 參考文獻 64 附錄 69 表一、歷史上著名的泡沫 69 表二、各國CPI資料表 70 表三、各國房市資料表 71 表四、各國實質股票資料表 73 表五、各國人均GDP資料表 74 表六、各國無風險資產資料表 76 | |
dc.language.iso | zh-TW | |
dc.title | 房市災難、經濟災難與股票溢酬之謎 | zh_TW |
dc.title | Housing Disasters, Economic Disasters, and Equity Premium Puzzle | en |
dc.type | Thesis | |
dc.date.schoolyear | 99-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 許耀文,曾惠斌 | |
dc.subject.keyword | 災難,房價,股票溢酬,資產定價, | zh_TW |
dc.subject.keyword | Disaster,Housing Price,Equity Premium,Asset Pricing, | en |
dc.relation.page | 77 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2011-07-27 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 土木工程學研究所 | zh_TW |
顯示於系所單位: | 土木工程學系 |
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