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題名 不動產投資風險衡量之研究
作者 黃瓊瑩
Huang , Chiung-ying
貢獻者 林秋瑾
Lin , Chiu-chin
黃瓊瑩
Huang , Chiung-ying
關鍵詞 不動產投資
風險衡量
風險值
real estate investment
measure risk
value at risk
日期 2003
上傳時間 14-Sep-2009 13:53:02 (UTC+8)
摘要 由於國民財富增加,對於不動產投資一事越來越熱衷,房屋不再只是供人居住使用,而成為重要的投資工具之一,但一般購屋投資者只考量投資『報酬』,卻忽略其『風險』,且由於傳統上對於投資不動產之風險只能以報酬率的標準差或變異數作計算,僅能知道其風險高或低,並不能夠確實知道其『風險值』,此外,投資者必須有分散風險之觀念,選擇適合的投資工具,以建立最佳的投資組合來分散風險。
      本文以『市場風險』為主,並以『購屋者投資』角度,探討國內外衡量不動產投資風險之估計方法、模型,找出風險因子以建立一套衡量不動產投資風險因子之模式,並估計風險值,以評估投資之可行性。以1975第1季年至2003年第4季之預售屋平均房價季資料為主軸之時間範圍,並以台北市為研究的地理範圍,以預售屋住宅為研究標的,並以購屋消費者角色作分析,運用各種風險衡量方法,包括樣本變異數法、指數加權移動平均法、GRACH模型、歷史模擬方法、蒙地卡羅結構法、拔靴法、GRACH-拔靴法及VAR-拔靴法等估計風險值。
     
      本文之實證結果顯示:
     
     一、以考量風險因子之VAR模型Ⅰ-拔靴法及VAR模型Ⅱ-拔靴法所估計之風險值最小,表示投資淨值一千萬元,有5﹪的機率可能的最大損失會大於591,218元或577,564元。
     
     二、以未考量風險因子之歷史模擬法及GARCH-拔靴法所估計風險值較大,表示投資淨值一千萬,有5﹪的機率可能的最大損失會大於2,816,827元或2,344,946元,因此,考量風險因子之VAR模型-拔靴法為較適當之模型,因有考量影響風險之因子,較能準確估計出實際之風險值。
     
     三、假設個案中估計調整後報酬率,在95﹪的信賴水準之下,未考慮風險因子模型估計之調整後報酬率為1.80﹪及2.32﹪,即持有一季後,調整後報酬約18及23萬元左右,而以考量風險因子之模型估計之調整後報酬率為2.37﹪及2.38﹪,即持有一季後報酬約24萬元左右。
     
     四、顯示投資組合於三種不同之投資工具時,當投資預售屋比例較大時,風險值是較小,而投資營建股價比例較大時,其風險值是較大。
As a result of national wealth increased, regarded real estate investment more and more desires, houses not only supply to live but also become one of investment tool, but general purchase investors only considered invest return but ignored risk at invest, as a result of traditional just estimated standard or variance of return represented risk, just to know the high or low of risk, but should not indeed to know the value at risk, investors must had concept of diversification, choose a appropriate investment tool and built the better portfolio to decrease risk.
     
      The current thesis was considered market risk and designed to examine the method or model of measure real estate risk, and looked for risk factors to build a set of model of real estate investment risk factors, and estimated value at risk to evaluate the feasible of investment. The current thesis used dates of time range are from 1975Q1 to 2003Q4, geography range is Taipei, pre-sales residential housing, and role of purchase consumer, apply many kinds of methods of measure risk, including Sample Variance, Exponentially Weighted Moving Average, Generalized Autoregressive Conditional Heteroskedasticity(GRACH), Historical Simulation Method, Monte Carlo Simulation, Classical Bootstrap, GARCH-Bootstrap and VAR-Bootstrap, to estimate value at risk.
     
      The empirical result showed that the first, there had minimum value at risk by considering VAR-Bootstrap of risk factors, represented investitive net value are NT 10,000,000, maximum loss of 5﹪probability will greater than NT 591,218 or NT 577,564. Secondly, there are bigger value at risk by Historical Simulation Method of risk-factors free, represented investitive net value are NT 10,000,000, maximum loss of 5﹪probability will greater than NT 2,816,827 or NT 2,344,946. So used considering VAR-Bootstrap of risk factors were more appropriated model, because model of considering risk factors were able to accurate estimate reality value at risk. The third, case study estimated adjusted return, at 95﹪confidence level, risk-factors estimated rate of adjusted return were 2.37﹪and 2.38﹪, hold one quarterly period the return about two hundred and forty thousand dollars, If we have not consider risk-factors, estimated rate of adjusted return were 1.80﹪and 2.32﹪, hold one quarterly period the return about one hundred and eighty thousand dollars or two hundred and thirty thousand dollars. The last, invest portfolio three kinds of investment tool, if invest ratio of pre-sales residential housing were bigger, then value at risk were smaller, and if invest ratio of construct stock were bigger, then value at risk were bigger.
參考文獻 一、中文部分
1.江明宜,(1997),營建類股價及其影響因素波動關係之研究-誤差修正模型之應用,碩士論文,國立政治大學地政學系。
2.江青穗,(1997),土地開發之財務分析,碩士論文,國立政治大學地政學系。
3.江義玄,(2000),投資組合之風險評價:新模擬方法的應用,國立政治大學企業管理學系。
4.何文榮譯,(1998),Zvi Bodie, Alex Kane, Alan J.J Marcus著,投資學,新陸書局。
5.周大慶、沈大白、張大成、敬永康、柯瓊鳳合著,(2002),風險管理新標竿-風險值理論與應用=The benchmark for Risk Management:Value at Risk,智勝文化。
6.周柏宏,(2002),建商老人住宅之財務分析-由開發與經營角度解析,碩士論文,國立政治大學地政學系。
7.林豐福、張開國、任維廉、陳菀蕙、葉又青、何慶生、王穎駿、雷治中、廖雅文、杜宗翰、喻世祥,(2002),應用風險管理於航空安全之研究,交通部運輸研究所。
8.段怡君,(1993),房地產投資報酬與風險相關性之研究,碩士論文,國立台灣工業技術學院管理技術研究所企業管理學程。
9.浦建亨,(2001),整合VaR法之衡量與驗證-以台灣金融市場投資組合為例,碩士論文,國立政治大學國際貿易學系。
10.翁玉芳,(2002),風險值衡量模型之研究-以農企業投資組合為例,碩士論文,國立屏東科技大學農企業管理。
11.張金鶚,(1997),房地產投資與決策分析-理論與實務,華泰書局。
12.郭遠志,(2002),購物中心開發財務風險評估模式之研究,碩士論文,朝陽科技大學建築及都市設計研究所。
13.陳力維,(2001),台灣房地產價格變動因素之研究,碩士論文,淡江大學金融學系。
14.黃佩玲,(1994),住宅價格與總體經濟變數關係之研究-以向量自我迴歸模式(VAR)進行實證,碩士論文,國立政治大學地政學系。
15.黃凰綺,(2003),應用風險值於休閒產業投資風險評估之研究-以開發休閒旅館為例,碩士論文,朝陽科技大學建築及都市設計研究所。
16.黃勝榮,(1989),風險情況下台北市不動產開發投資決策之研究-蒙地卡羅模擬方法之運用,碩士論文,國立政治大學地政研究所。
17.黃達業譯,(2001),Philippe Jorion著,風險值:市場風險控管之新基準,台灣金融研訓院。
18.楊宗翰,(2002),風險衡量系統之架構與建立,碩士論文,國立政治大學財務管理研究所。
19.楊雅婷,(2003),考量結構改變下之房價檢測與分析-以台北縣與台北市住宅價格為例,碩士論文,國立台北大學地政學系。
20.廖咸興、李阿乙、梅建平合著,(1999),不動產投資概論,華泰書局。
21.劉文祺、張淑怡、詹麗錦等,(2000),不同景氣循環階段最佳投資工具之選擇,台灣土地金融季刊,第三十七卷第四期,第45-67頁。
22.鄭佳音,(2000),台灣地區股價與房價之互動關係研究,碩士論文,淡江大學財務金融學系金融碩士班。
23.鄧家駒,(2002),風險管理,華泰文化事業公司。
24.賴麗華,(1996),住宅投資報酬率之研究,碩士論文,國立政治大學地政學系。
25.謝振耀,(2001),台灣債券投資組合風險值之評估,碩士論文,國立政治大學國際貿易學系。
26.叢文豪,(1995),影響房地產報酬率之風險因素及其敏感度之研究,碩士論文,國立台灣大學商學研究所。
二、英文部分
1.Dickey, D.A. and Fuller, W. A.(1979), “Distribution of the Estimates for Autoregressive Time Series With a Unit Root,” Journal of the American Statistical Association, 74:427-431.
2.Dickey, D.A. and Fuller, W. A.(1981), “Likelihood Ratio Statistics for Autoregressive time Series With a Unit Root,” Econometrica, 49:1057-1072.
3.Dickey, D.A., Bell W. and Miller, R.(1986), “Unit Root in Time Series Model:Tests and Implications,” American Statistican, 40:12-26.
4.Fuller, W.(1976), “Introduction to Statistical Series,” John Wiley and Sons:New York.
5.Ghysels, H. L. and Noh, J.(1994), “Testing for Unit Roots in Seasonal Time Series,” Journal of Econometrics, 62:415-442.
6.Hendershott, P. H. and Hendershott, R. J.(2002),“On Measuring Real Estate Risk,” Real Estate Finance, Winter:35-40.
7.Hylleberg, R. Engle, W. Granger, and B. Yoo(HEGY)(1990), “Seasonal Integration and Cointegration,” Journal of Econometrics, 44:215-238.
8.RATS 5.10 Software(2003), Estima, U.S.A.
9.Tsay, R. S.(2002), “Analysis of Financial Time Series,” Financial Econometrics.
10.Wheaton, W. C., Torto, R. G., Sivitanides, P. and Southard, J.(1999),“Evaluating Risk in Real Estate,”Real Estate Finance, Summer:15-22.
11.Wheaton, W. C.(2002),“On Measuring Real Estate Risk: A Reply,” Real Estate Finance, Winter:41-42.
12.Wheaton, W. C., Torto, R. G., Sivitanides, P., Southard, J. A., Hopkins, R. E. and Costello, J. M.(2001), “Real Estate Risk: A Forward-Looking Approach,” Real Estate Finance, Fall:20-28.
描述 碩士
國立政治大學
地政研究所
91257015
92
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0091257015
資料類型 thesis
dc.contributor.advisor 林秋瑾zh_TW
dc.contributor.advisor Lin , Chiu-chinen_US
dc.contributor.author (Authors) 黃瓊瑩zh_TW
dc.contributor.author (Authors) Huang , Chiung-yingen_US
dc.creator (作者) 黃瓊瑩zh_TW
dc.creator (作者) Huang , Chiung-yingen_US
dc.date (日期) 2003en_US
dc.date.accessioned 14-Sep-2009 13:53:02 (UTC+8)-
dc.date.available 14-Sep-2009 13:53:02 (UTC+8)-
dc.date.issued (上傳時間) 14-Sep-2009 13:53:02 (UTC+8)-
dc.identifier (Other Identifiers) G0091257015en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/32395-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 地政研究所zh_TW
dc.description (描述) 91257015zh_TW
dc.description (描述) 92zh_TW
dc.description.abstract (摘要) 由於國民財富增加,對於不動產投資一事越來越熱衷,房屋不再只是供人居住使用,而成為重要的投資工具之一,但一般購屋投資者只考量投資『報酬』,卻忽略其『風險』,且由於傳統上對於投資不動產之風險只能以報酬率的標準差或變異數作計算,僅能知道其風險高或低,並不能夠確實知道其『風險值』,此外,投資者必須有分散風險之觀念,選擇適合的投資工具,以建立最佳的投資組合來分散風險。
      本文以『市場風險』為主,並以『購屋者投資』角度,探討國內外衡量不動產投資風險之估計方法、模型,找出風險因子以建立一套衡量不動產投資風險因子之模式,並估計風險值,以評估投資之可行性。以1975第1季年至2003年第4季之預售屋平均房價季資料為主軸之時間範圍,並以台北市為研究的地理範圍,以預售屋住宅為研究標的,並以購屋消費者角色作分析,運用各種風險衡量方法,包括樣本變異數法、指數加權移動平均法、GRACH模型、歷史模擬方法、蒙地卡羅結構法、拔靴法、GRACH-拔靴法及VAR-拔靴法等估計風險值。
     
      本文之實證結果顯示:
     
     一、以考量風險因子之VAR模型Ⅰ-拔靴法及VAR模型Ⅱ-拔靴法所估計之風險值最小,表示投資淨值一千萬元,有5﹪的機率可能的最大損失會大於591,218元或577,564元。
     
     二、以未考量風險因子之歷史模擬法及GARCH-拔靴法所估計風險值較大,表示投資淨值一千萬,有5﹪的機率可能的最大損失會大於2,816,827元或2,344,946元,因此,考量風險因子之VAR模型-拔靴法為較適當之模型,因有考量影響風險之因子,較能準確估計出實際之風險值。
     
     三、假設個案中估計調整後報酬率,在95﹪的信賴水準之下,未考慮風險因子模型估計之調整後報酬率為1.80﹪及2.32﹪,即持有一季後,調整後報酬約18及23萬元左右,而以考量風險因子之模型估計之調整後報酬率為2.37﹪及2.38﹪,即持有一季後報酬約24萬元左右。
     
     四、顯示投資組合於三種不同之投資工具時,當投資預售屋比例較大時,風險值是較小,而投資營建股價比例較大時,其風險值是較大。
zh_TW
dc.description.abstract (摘要) As a result of national wealth increased, regarded real estate investment more and more desires, houses not only supply to live but also become one of investment tool, but general purchase investors only considered invest return but ignored risk at invest, as a result of traditional just estimated standard or variance of return represented risk, just to know the high or low of risk, but should not indeed to know the value at risk, investors must had concept of diversification, choose a appropriate investment tool and built the better portfolio to decrease risk.
     
      The current thesis was considered market risk and designed to examine the method or model of measure real estate risk, and looked for risk factors to build a set of model of real estate investment risk factors, and estimated value at risk to evaluate the feasible of investment. The current thesis used dates of time range are from 1975Q1 to 2003Q4, geography range is Taipei, pre-sales residential housing, and role of purchase consumer, apply many kinds of methods of measure risk, including Sample Variance, Exponentially Weighted Moving Average, Generalized Autoregressive Conditional Heteroskedasticity(GRACH), Historical Simulation Method, Monte Carlo Simulation, Classical Bootstrap, GARCH-Bootstrap and VAR-Bootstrap, to estimate value at risk.
     
      The empirical result showed that the first, there had minimum value at risk by considering VAR-Bootstrap of risk factors, represented investitive net value are NT 10,000,000, maximum loss of 5﹪probability will greater than NT 591,218 or NT 577,564. Secondly, there are bigger value at risk by Historical Simulation Method of risk-factors free, represented investitive net value are NT 10,000,000, maximum loss of 5﹪probability will greater than NT 2,816,827 or NT 2,344,946. So used considering VAR-Bootstrap of risk factors were more appropriated model, because model of considering risk factors were able to accurate estimate reality value at risk. The third, case study estimated adjusted return, at 95﹪confidence level, risk-factors estimated rate of adjusted return were 2.37﹪and 2.38﹪, hold one quarterly period the return about two hundred and forty thousand dollars, If we have not consider risk-factors, estimated rate of adjusted return were 1.80﹪and 2.32﹪, hold one quarterly period the return about one hundred and eighty thousand dollars or two hundred and thirty thousand dollars. The last, invest portfolio three kinds of investment tool, if invest ratio of pre-sales residential housing were bigger, then value at risk were smaller, and if invest ratio of construct stock were bigger, then value at risk were bigger.
en_US
dc.description.tableofcontents 中文摘要……………………………………………………………………Ⅰ
     英文摘要……………………………………………………………………Ⅲ
     謝誌…………………………………………………………………………Ⅴ
     目錄…………………………………………………………………………Ⅶ
     
     第一章 緒論………………………………………………………………1
      第一節 研究動機與目的………………………………………………1
      第二節 研究問題與範圍………………………………………………3
      第三節 研究方法………………………………………………………4
      第四節 研究架構與流程………………………………………………5
     第二章 理論與文獻回顧…………………………………………………7
      第一節 風險理論………………………………………………………7
      第二節 風險之概念與定義……………………………………………13
      第三節 風險值衡量之方法……………………………………………20
      第四節 投資風險相關文獻整理與探討………………………………33
      第五節 小結……………………………………………………………38
     第三章 不動產投資風險值之衡量……………………………………39
      第一節 資料說明………………………………………………………39
      第二節 各種風險值衡量之實證分析…………………………………42
      第三節 小結……………………………………………………………50
     第四章 不動產投資風險影響因子模式之建立…………………………51
      第一節 模型之建立……………………………………………………51
      第二節 風險因子之選取………………………………………………56
      第三節 考慮風險因子模型之實證分析………………………………67
      第四節 考慮風險因子之投資風險值衡量實證分析…………………78
      第五節 小結……………………………………………………………82
     第五章 投資組合分析……………………………………………………83
      第一節 資料說明………………………………………………………83
      第二節 投資組合風險值衡量之實證分析……………………………88
      第三節 小結……………………………………………………………93
     第六章 結論與建議………………………………………………………95
     第一節 結論與建議……………………………………………………95
     第二節 後續研究………………………………………………………98
     附錄…………………………………………………………………………99
     參考文獻……………………………………………………………………107
zh_TW
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0091257015en_US
dc.subject (關鍵詞) 不動產投資zh_TW
dc.subject (關鍵詞) 風險衡量zh_TW
dc.subject (關鍵詞) 風險值zh_TW
dc.subject (關鍵詞) real estate investmenten_US
dc.subject (關鍵詞) measure risken_US
dc.subject (關鍵詞) value at risken_US
dc.title (題名) 不動產投資風險衡量之研究zh_TW
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 一、中文部分zh_TW
dc.relation.reference (參考文獻) 1.江明宜,(1997),營建類股價及其影響因素波動關係之研究-誤差修正模型之應用,碩士論文,國立政治大學地政學系。zh_TW
dc.relation.reference (參考文獻) 2.江青穗,(1997),土地開發之財務分析,碩士論文,國立政治大學地政學系。zh_TW
dc.relation.reference (參考文獻) 3.江義玄,(2000),投資組合之風險評價:新模擬方法的應用,國立政治大學企業管理學系。zh_TW
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