(3.237.178.91) 您好!臺灣時間:2021/03/07 14:58
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
: 
twitterline
研究生:李曉玲
研究生(外文):Hsiao Lin Lee
論文名稱:風險值的應用:以REITs產業為例
論文名稱(外文):The Application of Value at Riak (VaR): The Case of REITs
指導教授:盧秋玲盧秋玲引用關係
指導教授(外文):Chiuling Lu
學位類別:碩士
校院名稱:元智大學
系所名稱:財務金融研究所
學門:商業及管理學門
學類:財務金融學類
論文種類:學術論文
論文出版年:2004
畢業學年度:92
語文別:英文
中文關鍵詞:風險值不動產投資信託移動加權平均法指數加權平均法歷史模擬法拔靴複製法
外文關鍵詞:Value-at-Riskreal estate investment trust (REITs)the equally weighted moving averagethe exponentially weighted moving averagehistorical simulationbootstrap
相關次數:
  • 被引用被引用:9
  • 點閱點閱:168
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
這篇研究應用了四種計算風險值的方法,移動加權平均法、指數加權平均法、歷史模擬法及拔鞡複製法,來衡量十二個不動產投資信託投資組合的市場風險,分別以95%及99%的信賴水準計算持有期間為每日與十天的風險值,同時,運用回顧測試來驗證模型的正確性,研究發現拔鞡複製法在信賴水準為99%產生最正確的風險值,但是四種模型在95%的信賴水準沒有估算出精確的風險值,因此,在99%的信賴水準下,應使用歷史模擬法或拔鞡複製法來估算不同型態的不動產投資信託投資組合的每日風險值,當持有期間是十天時,我們建議移動加權平均法、指數加權平均法使用95%的信賴水準。
This paper employs four VaR methodologies, the equally weighted moving average (SMA), the exponentially weighted moving average (EWMA), historical simulation and bootstrap methods to measure the downside market risk of a total of twelve real estate investment trust (REITs) portfolios. The one-day horizon and two-week holding period VaRs are estimated separately for both 95% and 99% confidence levels. Then, we apply the backtesting of Basel rules to verify these models. We find that the bootstrap method produces the most precise VaRs at the 99% confidence level. In addition, the four models don’t forecast VaRs accurately for each portfolio at the 95% confidence level. For the portfolios formed by different property types or different leverage ratios, we suggest that one-day VaRs should be estimated by the historical simulation or the bootstrap method at the 99% confidence level. Finally, the parametric approaches produce more reliable two-week holding period VaRs at a 95% confidence level.
Table of Contents
1. Introduction-----------------------------------------------------------------01
2. Literatures-------------------------------------------------------------------02
3. Data---------------------------------------------------------------------------04
4. Introduction to Value-at-Risk Models---------------------------------05
4.1 The Delta-Normal Approach------------------------------------------06
4.2 Equally Weighted Moving Average (SMA)-------------------------07
4.3 Exponentially Weighted Moving Average (EWMA)--------------07
4.4 Historical Simulation (HS)--------------------------------------------08
4.5 Bootstrap Method-------------------------------------------------------09
5. Result------------------------------------------------------------------------10
6. Conclusion------------------------------------------------------------------14
Reference----------------------------------------------------------------------- 15
Alexander, C.O., and C.T. Leigh. (1997) “On the Covariance Models used in Value at Risk Models.” Journal of Derivative, Vol. 4 No. 3, pp.50-62.
Ammann, M., and C. Reich. (2001) "VaR for Nonlinear Financial Instruments - Linear Approximation or full Monte Carlo ? " Financial Markets and Portfolio Management, Vol. 15, No. 3, pp.363-378.
Beder, Tanya Styblo. (1995) "VaR: Seductive but Dangerous." Financial Analysis Journal, Vol. 51, No.5, pp.12-24.
Brooks, C., and G. Persand. (2000) “Value at Risk and Market Crashes.” Journal of Risk, Vol.2, pp.5-26.
Brooks, C.. and G. Persand. (2002) “Model Choice and Value-at-Risk Performance.” Financial Analysts Journal, Vol. 58, No. 5, pp.87-97.
Brooks, C., and G. Persand. (2003) "The Effect of Asymmetries on Stock Index Return Value at Risk Estimates." Journal of Risk Finance, 4(2), pp. 29-42.
Davidson, A.C., and D.V. Hinkley. (1997) “Bootstrap Methods and Their Application.” Cambridge University Press.
Duffie, D., and J. Pan. (1997) “An Overview of Value-at-Risk.” Journal of Derivatives, Vol. 4, No. 3, pp.7-49.
Efron, B., and R.J. Tibshirani. (1993) “An Introduction to the Bootstrap.” Chapman and Hall.
Elgonemy, A.R. (2000) “Real Estate Investment Trust in 2000.” RKF Consulting.
Gordon, J. N., and E.W.K. Tse. (2003), “VaR: A Tool to Measure Leverage Risk.” Journal of Portfolio Management, Vol. 29, No. 25, pp.62-65.
Hendricks, D. (1996) “Evaluation of Value-at-Risk Models Using Historical Data.” Federal Reserve Bank of New York Economic Policy Review, Vol. 2, No.1, pp.39-69.
Hull, J., and A. White. (1998) “Value at Risk When Daily Changes in Market Variables Are Not Normally distributed.“ Journal of Derivatives, Vol. 5, No.3, pp.9-19.
Jackson, P., D.J Maude, and W. Perraudin. (1997) “Bank Capital and Value at Risk.” Journal of Derivatives, Vol. 4 No. 3, pp.73-90.
Johansson, F., M.J. Sieler, and M. Tjarnberg. (1999) “Measuring Downside Portfolio Risk.” Journal of Portfolio Management, Vol. 26, No. 1, pp. 96-107.
Jorion, P. (1997) “Value at Risk: the New Benchmark for Managing Financial Risk.” McGraw-Hill.
Lu, Yang-Cheng, and Yun-Yung Lin, (1999) “A Nested VaR Bootstrapping with Fat Tail Correction for Equity Portfolio in Taiwan.“ Fifth Annual Conference on Pacific Basin Economics, Finance and Accounting, May 1999, Taipei.
Martinez, B. (1998) “REITs Begin Adding New Debt to Pay for Coming Acquisitions.” The Wall Street Journal Interactive Edition.
Siegl, T., and A. West. (2001) “Statistical Bootstrapping Methods in VaR Calculation.” Applied Mathematical Finance 8, pp.167-181.
Vlaar, P.J.G. (2000) “Value at Risk Models for Dutch Bond Portfolios.” Journal of Banking and Finance, 24, pp.1131-1154.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
系統版面圖檔 系統版面圖檔