Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/32556
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dc.contributor.advisor劉明郎zh_TW
dc.contributor.author楊芯純zh_TW
dc.contributor.authorShin-Chuen Yangen_US
dc.creator楊芯純zh_TW
dc.creatorShin-Chuen Yangen_US
dc.date2002en_US
dc.date.accessioned2009-09-17T05:44:38Z-
dc.date.available2009-09-17T05:44:38Z-
dc.date.issued2009-09-17T05:44:38Z-
dc.identifierG0089751003en_US
dc.identifier.urihttps://nccur.lib.nccu.edu.tw/handle/140.119/32556-
dc.description碩士zh_TW
dc.description國立政治大學zh_TW
dc.description應用數學研究所zh_TW
dc.description89751003zh_TW
dc.description91zh_TW
dc.description.abstract本文提出一個新的混合整數線性規劃模型建立投資組合。這個模型所採用的風險函數為最大損失的絕對值,而不是一般常用的損失變異數。在給定的報酬水準下,模型尋找在觀測期間中最小的最大損失的投資組合,即為大中取小的原則。模型也同時考慮實務上常遇見之情況,如:交易成本、最小交易單位、固定交易費用比率、資產總類數等限制。因此,模型內需使用整數變數及二元變數,導致模型的計算求解過程變得比不含整數變數及二元變數的模型困難許多。我們以固定整數變數的啟發式演算法增進求解的效率,並以台灣股票市場的資料做為實證計算的對象。zh_TW
dc.description.abstractA new mixed integer linear program (MILP) for selecting portfolio based on historical return is proposed. This model uses the downside risk rather than the variance as a risk measure. The portfolio is chosen that minimizes the maximum downside risk over all past observation periods to reach a given return level. That is a mini-max principle. The model incorporates the practical characteristics such as transaction costs, minimum transaction units, fixed proportional transaction rates, and cardinality constraint. For this reason a set of integer variables and binary variables are introduced. The introduction, however, increases the computational complexity in model solution. Due to the difficulty of the MILP problem, a heuristic algorithm has been developed for the solution. The computational results are presented by applying the model to the Taiwan stock market.en_US
dc.description.tableofcontents摘要 iii\nABSTRACT iv\n表目錄 vi\n圖目錄 vii\n第一章 緒論 1\n 1.1 前言 1\n 1.2 研究的目的與架構 2\n第二章 文獻回顧 3\n第三章 相關模型探討 8\n 3.1 Markowitz模型 8\n 3.2 Konno-Yamazaki模型 9\n 3.3 Young模型 15\n第四章 大中取小法的規劃模型 18\n 4.1 不含實際交易限制的模型 18\n 4.2 含實際交易限制的模型 21\n第五章 啟發式演算法與實證的結果與討論 25\n 5.1 啟發式演算法 25\n 5.2 大中取小投資組合的效能與討論 26\n 5.3 實證的結果與討論 26\n第六章 結論與建議 32\n參考文獻 33\n附錄 附表 35zh_TW
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dc.language.isoen_US-
dc.source.urihttp://thesis.lib.nccu.edu.tw/record/#G0089751003en_US
dc.subject大中取小原則zh_TW
dc.subject投資組合優化zh_TW
dc.subject混合整數線性規劃zh_TW
dc.subjectmini-max principleen_US
dc.subjectportfolio optimizationen_US
dc.subjectmixed integer linear programen_US
dc.title大中取小法建立最佳投資組合zh_TW
dc.titlePortfolio Optimization Using Minimax Selection Ruleen_US
dc.typethesisen
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dc.relation.referenceKonno, H. and H. Yamazaki, Mean-absolute deviation portfolio optimization model and its applications to Tokyo stock market, Management Science 37, 519-531 (1991).zh_TW
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dc.relation.referenceMarkowitz, H., Portfolio selection, Journal of Finance 7, 77-91 (1952).zh_TW
dc.relation.referenceMarkowitz, H., Portfolio selection (2nd ed.), Blackwell, Cambridge, MA(1991).zh_TW
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dc.relation.referenceXia, Y., B. Liu, S. Wang and K. K. Lai, A model for portfolio selection with order of expected returns, Computers & Operations Research 27, 409-422 (2000).zh_TW
dc.relation.referenceYoung, M. R., A minimax portfolio selection rule with linear programming solution, Management Science 44, 673-683 (1998).zh_TW
dc.relation.referenceYu, G., Min-max optimization of several classical discrete optimization problems, Journal of Optimization Theory and Applications 98, 221-242 (1998).zh_TW
dc.relation.reference呂建鴻,考量下層風險的最佳投資組合,國立政治大學應用數學研究所碩士論文 (民91)。zh_TW
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