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研究生:張維元
研究生(外文):Chang, Wei-Yuan
論文名稱:考慮多準則的模糊投資組合重新調整模型
論文名稱(外文):Fuzzy portfolio rebalancing model with multiple criteria
指導教授:余菁蓉余菁蓉引用關係
指導教授(外文):Yu, Jing-Rung
口試委員:林張群曾國雄江勁毅
口試委員(外文):Lin, Chang-ChunTzeng, Gwo-HshiungChiang, Chin-I
口試日期:2011-07-28
學位類別:碩士
校院名稱:國立暨南國際大學
系所名稱:資訊管理學系
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2011
畢業學年度:99
語文別:中文
論文頁數:50
中文關鍵詞:偏態模糊理論重新調整賣空交易成本
外文關鍵詞:skewnessfuzzy theoryrebalancingshort saletransaction cost
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為解決資產報酬資料的變動所造成的資料不確定性問題,本研究利用模糊數表示個別資產的報酬率,針對投資組合,考慮了投資報酬、風險、偏態與賣空等多個決策因素,並設定了各投資權重的上下限。此外,為了更貼近實際交易情形,提出了考慮交易成本的投資組合重新調整模型,以模擬股票市場的實際交易情形。因此,本研究提出了同時考慮投資報酬、風險、偏態、賣空與交易成本的多準則模糊投資組合重新調整模型。實例分析中,以台灣與紐約證券交易所中的股票資料來做投資組合的分析,透過每期權重重新調整後所求出的市場價值,來比較投資組合模型中,偏態與賣空對於投資組合價值的影響。最後,本篇論文的貢獻在於解決投資報酬為不精確時,多準則考量投資組合的情形,並證明在投資組合中考慮投資偏態與投資賣空能讓模型產生較高的績效。
In order to deal with the uncertainty issue in returns, fuzzy variables are employed to indicate the assets’ return rate and consider portfolio return, as well as risk and skewness in the portfolio. To approach a real transaction, the criteria of the short sale and transaction cost in the portfolio are considered simultaneously. Therefore, a rebalancing model with multiple criteria, including return, risk, skewness, short sale proportion, and transaction cost in portfolio selection is proposed. Two data sets, from Taiwan and the New York Stock Exchange, are analyzed and compared to find the impact when skewness and short sales are considered in a fuzzy portfolio model. The contribution of this article is to solve a multiple criteria portfolio when the return data has fuzzy variables and to prove that it can generate a better result when considering skewness and short sales in portfolio selection.
摘要 I
Abstract II
目錄 III
圖目錄 IV
表目錄 V
第一章 序論 1
1.1 研究背景與動機 1
1.2 論文組織與架構 3
第二章 文獻探討 4
2.1 傳統均異模型 4
2.2 投資組合重新調整的線性規劃模型 4
2.3 模糊形式投資組合模型 8
第三章 考量報酬不確定性的投資組合重新調整模型 10
第四章 實證分析 18
4.1:台灣50成分股 18
4.1.1:FMV_Sk、FMVS與FMVS_Sk模型的績效比較 20
4.1.2:使用重新調整策略與使用Buy & Hold策略的比較 28
4.1.3:考量多目標模型與Li et al. (2010)單目標模型比較 29
4.2:台灣50+中型100成分股 29
4.3:S&P 500成分股 36
第五章 結論 44
參考文獻 45
附錄 49

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