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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/10236完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 劉淑鶯 | |
| dc.contributor.author | Meng-Yu Chan | en |
| dc.contributor.author | 詹孟諭 | zh_TW |
| dc.date.accessioned | 2021-05-20T21:12:47Z | - |
| dc.date.available | 2011-03-01 | |
| dc.date.available | 2021-05-20T21:12:47Z | - |
| dc.date.copyright | 2011-02-20 | |
| dc.date.issued | 2011 | |
| dc.date.submitted | 2011-02-13 | |
| dc.identifier.citation | Reference
Brinson, G. P., B. D. Singer, and G. L. Beebower (1991), “Determinants of Portfolio Performance: An Update”, Financial Analysts Journal, Vol. 47, pp. 40-48. Chopra, V. K. and W. T. Ziemba (1993), “The Effect of Errors in Means, Variances and Covariance on Optimal Portfolio Choice”, Journal of Portfolio Management, Vol. 19, pp. 6-11. Elam, E. and B. L. Dixon (1988), “Examining the Validity of a Test of Futures Market Efficiency, Journal of Futures Markets, Vol. 8, pp. 365-372 Engle, R. F. and C. W. J. Granger (1987), “Co-integration and Error Correction: Representation, Estimation and Testing,” Econometrica, Vol. 55, pp. 251-276. Granger, C. W. J. and P. Newbold (1974), “Spurious Regressions in Economics.” Journal of Econometrics, Vol. 2, pp. 111-120. Li, D. and W. L. Ng (2000), “Optimal Dynamic Portfolio Selection: Multiperiod Mean-Variance Formulation”, Mathematical Finance, Vol. 10, pp. 387-406 Markowitz, H. M. (1952), “Portfolio Selection”, Journal of Finance, Vol. 7, pp. 77-91. Melanie, B. R. (2008), “A Dynamic Programming Approach to Two-Stage Mean-Variance Portfolio Selection in Cointegrated Vector Autoregressive Systems”, 47th IEEE Conference on Decision and Control Cancun, Mexico, Dec. 9-11. Michaud, R. O. (1989), “The Markowitz Optimization Enigma: Is Optimized Optimal?” Financial Analysts Journal, Vol. 45, pp. 31-42. Nelson, C. R. and C. Plosser (1982), “Trends and Random Walks in Macroeconomic Time Series: Some Evidence and Implications,” Journal of Monetary Economics, Vol. 10, pp. 139-167. Scherer, B. (2002), “Portfolio Resampling: Review and Critique”, Financial Analysts Journal, Vol. 58, pp. 98-109. Wolf, M. (2006), “Resampling vs. Shrinkage for Benchmarked Managers”, Working paper, No. 263, Institute for Empirical Research in Economics University of Zurich, Working Paper Series, ISSN 1424-0459. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/10236 | - |
| dc.description.abstract | 本文的資產價格數列模型，採用PCB 共整合模型，將它整理成VAR(1)的型式，式子中的參數，必須符合本文的公式，然後我們藉由這個模型，使用Markowitz(1952)提出的平均數－變異數最佳化方法(Mean－Variance optimization approach)－固定風險、求報酬最大化的目標下，延伸作多期資產配置，再分別對一階段方法、二階段方法作討論。在有交易成本及截距項的情況下，比較這二種方法，同樣風險下的淨期望報酬。另外也比較，在特殊例子下，一階段方法與二階段方法，何種方法在同樣的風險下，能為我們帶來較大的淨期望報酬。 | zh_TW |
| dc.description.abstract | This paper uses the PCB Cointegration Model to organize the sequence information of the price of financial commodity into the VAR(1) type. The parameters in the formula VAR(1) must meet the formulas in this paper. We extend Markowitz’s mean-variance optimization approach published in 1952, which is to maximize the return under the fixed risk, to multi-stage asset allocation, and use this new model to discuss the one-stage method and the two-stage method. The paper then compares the net returns of the two methods when undertaking the same risk, under the condition of transaction cost and intercept. We will also examine the one-stage method and the two-stage method in the special cases to determine which one can bring the better net expected return under the same risk. | en |
| dc.description.provenance | Made available in DSpace on 2021-05-20T21:12:47Z (GMT). No. of bitstreams: 1 ntu-100-R96221043-1.pdf: 1306558 bytes, checksum: 69b1c6f926ad1a434598384e2b284345 (MD5) Previous issue date: 2011 | en |
| dc.description.tableofcontents | Contents
Chapter 1 Introduction 1 1.1 Motivation and purpose 1 1.2 Framework 5 Chapter 2 The Cointegration model 8 Chapter 3 Research Method 10 3.1 Notations 10 3.2 Objective functions 11 3.3 Dynamic portfolio selection methods 13 3.3.1 One-stage method 13 3.3.2 Two-stage method 15 3.4 Special cases 20 Chapter 4. Numerical Illustrations 25 4.1 Unit root test and cointegration test 25 4.2 Parameter estimation 26 4.3 Transaction costs 27 4.4 Numerical results 28 4.4.1 Results of one-stage method 28 4.4.2 Results of two-stage method 29 4.5 Method comparisons 30 Chapter 5 Conclusions and Recommendations 33 Reference 36 Appendix 38 Contents of Appendix Appendix 1. One-stage method 38 Appendix1.1． 38 Appendix1.1.1．Obtained the initial estimate by Taylor expansion 38 Appendix1.1.2．The identical equation sorts out from the formula 39 Appendix1.2． 39 Appendix1.3． ....................................................................................40 Appendix1.3.1．One-stage method of the maximum return method 40 Appendix1.3.2．One-stage method of the minimum variance method 42 Appendix1.4． 42 Appendix2. Two-stage method 43 Appendix2.1． 43 Appendix2.1.1．Deriving the vector of expected return and the matrices of variance and expected transaction cost 43 Appendix2.1.2．Obtained the initial estimate by Taylor expansion 47 Appendix2.1.3．The identical equation sorts out from the formula 48 Appendix2.2． 49 Appendix2.3． 51 Appendix2.3.1．Two-stage method of the maximum return method 51 Appendix2.3.2．Two-stage method of the minimum variance method.…….52 Appendix2.4． 55 Contents of Figure Figure 1. Framework………………………………………………………………….. ...7 Contents of Table Table 1. Comparison of expected net return……..…………………………..................31 Table 2. Comparison of expected net return……..…………………………..................32 Table 3. Comparison of expected net return……..…………………………..................33 Table 4. Comparison of net return and the return per risk unit under ……..…………………………...............................................33 | |
| dc.language.iso | en | |
| dc.title | 共整合向量模型之平均數-變異數動態投資組合方法探討 | zh_TW |
| dc.title | Dynamic Approaches to Mean-Variance Portfolio Selection
in Cointegrated Vector Autoregressive Systems | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 99-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 彭柏堅,鄭天澤 | |
| dc.subject.keyword | PCB 共整合模型,Markowitz平均數－變異數最佳化方法,多期資產配置,一階段方法,二階段方法, | zh_TW |
| dc.subject.keyword | PCB Cointegration Model,Markowitz Mean-Variance OptimizationApproach,Multi-stage Asset Allocation,One-stage Method,Two-stageMethod, | en |
| dc.relation.page | 55 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2011-02-14 | |
| dc.contributor.author-college | 理學院 | zh_TW |
| dc.contributor.author-dept | 數學研究所 | zh_TW |
| 顯示於系所單位： | 數學系 | |
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|---|---|---|---|
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