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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 周國端 | |
| dc.contributor.author | Ming-Hsiu Yu | en |
| dc.contributor.author | 游明修 | zh_TW |
| dc.date.accessioned | 2021-06-08T05:57:38Z | - |
| dc.date.copyright | 2009-03-23 | |
| dc.date.issued | 2007 | |
| dc.date.submitted | 2007-10-02 | |
| dc.identifier.citation | 1. Bevan, A. and Winkelmann, K. (1998), ”Using the Black-Litterman Global Asset allocation: Three Years of Practical Experience”, Goldman Sachs & Co.
2. Beach S. L. and Orlov, A. G. (2006), “An Application of the Black-Litterman Model with EGARCH-M-Derived Views for International Portfolio Management”, Radford University. 3. Black, F. and Litterman, R. (1991), “Global Asset Allocation with Equities, Bonds, and Currencies”, Goldman Sachs & Co. 4. Black, F. and Litterman, R. (1992), “Global Portfolio Optimization”, Financial Analyst Journal. 5. Chou, P.H., Li, W.S. and Zhou, G. (2000), “Factors, Characteristics, and Portfolio”, National Central University. 6. Christodoulakis, G. A. (2002), “Bayesian Optimal Portfolio Selection: the Black-Litterman Approach”, City University, London. 7. Drobetz, W. (2001), “How to Avoid the Pitfalls in Portfolio Optimization? Putting the Black-Litterman Approach at Work”, Financial Markets and Portfolio Management. 8. Figelman, I. (2004), “Optimal Active Risk Budgeting Model”, Journal of Portfolio Management. 9. He, G. and Litterman, R. (1999), ”The Intuition Behind Black-Litterman Model Portfolios”, Goldman Sachs & Co. 10. Idzork, T. (2002), “A Step-By-Step Guide to the Black-Litterman Model”, Duke University. 11. Iordanidis, K. (2002), “Global Asset Allocation Portfolio Construction and Risk Management. 12. Jones, R., Lim, T. and Zangari, P.J. (2007), “The Black-Litterman Model for Structured Equity Portfolios”, Journal of Portfolio Management. 13. Litterman, R. and Winkelmann, K. (1996) “Risk Management Series：Estimating Market Exposure”, Goldman Sachs & Co. 14. Mankert, C. (2006), “The Black-Litterman Model – Mathematical and Behavioral Finance Approaches towards Its Use in Practice”, Royal Institute of Technology. 15. Palomba, G. (2007),”Multivariate GARCH Models and Black-Litterman Approach for Tracking Error Constrained Portfolios: An Empirical Analysis”, Universita Politecnica delle Marche. 16. Roll, R. (1992), “A Mean/Variance Analysis of Tracking Error”, Journal of Portfolio Management. 17. Markowitz, H. (1952), “Portfolio Selection”, Journal of Finance. 18. Sharpe, W.F. (1964), “Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of Risk”, Journal of Finance. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/24873 | - |
| dc.description.abstract | 本研究探討兩階層資產配置模型應用於保險業內部基金建構之樣本外績效，試圖透過兩階層配置，將市場報酬與經理人主動報酬分離進行配置，以期將投資組合之組成結構化。在第一階層部分，本研究利用Black-Litterman模型進行配置，此模型特點為結合長期市場均衡報酬及投資者展望，以形成預期報酬及共變異數，並據此建立投資組合。其中的投資者展望部分，本研究以短期之動能策略產生兩組預期，分別為自我回歸與歷史平均模型。在第二階層部分，本研究利用Alpha-Tracking Error 最適化模型進行配置，此模型特點為採用經理人主動報酬與追蹤誤差進行最適化資產配置。實證分析部分，以五個區域型股票市場以及對應之共同基金為研究對象，研究期間為2000年1月至2006年12月，共分四種情境進行探討。投資組合依據前一年之歷史資料進行參數估計，投資期間為三年，同時每兩週進行資產重新配置。本研究採用之指標投資組合為市場權重投資組合與使用歷史資料進行Markowitz均異分析配置之市場模擬投資組合。主要的實證結果如下：
1. 就短期之動能策略而言，自我回歸模型績效顯著高於歷史平均模型。 2. 就信心水準而言，在市場呈現空頭或盤整走勢時，兩種動能策略皆以較低之信心水準投資組合表現較佳；而在市場呈現多頭或拉回走勢時，自我回歸模型中100%信心水準投資組合表現較佳，而歷史平均模型則不顯著。 3. Black-Litterman模型可有效降低投資組合報酬之波動性與市場暴險。 4. 在第二階層之基金組合中，各子投資組合之風險調整後報酬表現顯著高於各市場指數。 整體而言，本研究採用之兩階層資產配置模型績效較指標投資組合為佳。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2021-06-08T05:57:38Z (GMT). No. of bitstreams: 1 ntu-96-R94723070-1.pdf: 437340 bytes, checksum: 46ca7a19da2f2757f5045fc008af0ff4 (MD5) Previous issue date: 2007 | en |
| dc.description.tableofcontents | CHAPTER 1 — INTRODUCTION 1
1.1 MOTIVATION AND BACKGROUND 1 1.2 OBJECTIVE 4 1.3 ORGANIZATION 5 CHAPTER 2 — LITERATURE REVIEW 6 2.1 MARKOWITZ MEAN-VARIANCE ANALYSIS 6 2.2 BLACK-LITTERMAN MODEL 7 2.3 ALPHA-TRACKING ERROR OPTIMIZATION 9 CHAPTER 3 — MODEL SPECIFICATION AND METHODOLOGY 10 3.1 METHODOLOGY 10 3.1.1 Markowitz Mean-Variance Analysis 11 3.1.2 The Black-Litterman Model 12 3.1.3 Alpha-Tracking Error Optimization 19 3.2 PERFORMANCE EVALUATION AND RISK ANALYSIS OF THE PORTFOLIO 20 3.2.1 Comparative Model 20 3.2.2 Performance Evaluation and Risk Analysis 21 CHAPTER 4 — EMPIRICAL RESULT 24 4.1 DATA 24 4.1.1 Research subjects and periods of data 24 4.1.2 Source of data 25 4.2 RESEARCH DESIGN AND PROCESS 26 4.3 RESULT 31 4.3.1 Second Layer Sub-Portfolio Performance Evaluation and Risk Analysis 31 4.3.2 First Layer Portfolio Performance Evaluation and Risk Analysis 36 CHAPTER 5 — CONCLUSION 44 5.1 IN THE SECOND LAYER 44 5.2 IN THE FIRST LAYER 45 BIBLIOGRAPHY 47 APPENDIX I 49 | |
| dc.language.iso | en | |
| dc.title | 兩階段資產配置應用於內部基金建置 | zh_TW |
| dc.title | Two-Layer Asset Allocation Applied to the Internal Fund Organization – Combined the Black-Litterman Model with the Alpha-Tracking Error Optimization | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 96-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 吳志遠,謝明華 | |
| dc.subject.keyword | 資產配置,內部基金, | zh_TW |
| dc.subject.keyword | Asset Allocation,Internal Fund,Markowitz,Black-Litterman,Alpha,Tracking Error, | en |
| dc.relation.page | 48 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2007-10-03 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 財務金融學研究所 | zh_TW |
| 顯示於系所單位： | 財務金融學系 | |
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