臺灣博碩士論文加值系統

Markowitz(1952)提出平均數-變異數投資組合模型架構(Mean-Variance Portfolio Framework)，融券行為卻無法直接利用此模型，且目前有關股票信用交易之相關研究大多偏重於買進持有(Long position)之探討，鮮少著重融券放空(Short position)之行為的研究。因此，本研究提出四個模式，以MV模型為基礎，並且放寬融券行為的限制做一應用。第一、即允許融券行為，期望為投資組合帶來較高的收益，但希望降低融券的支數，進而降低融券行為本身所伴隨的高風險特性；第二、在考量融券行為下，進一步降低融券在投資組合中的比例；第三、加入了重新規劃法(De Novo programming)，能提供為消除獲利與風險的衝突而重新調整預算，使所得投資組合將能提供更臻完善的選股策略；第四，將獲利、風險、融券支數和全部選股支數視為四個準則，利用多目標規劃方式同時滿足這四個準則，以提供一個多目標最佳化的投資組合。最後將會以兩個台灣股票市場的資料集作為驗證，由分析結果顯示，所求出的投資組合不但都能達成上述目標，並且能藉由加入融券行為而提升獲利、分擔風險，為提供投資人更精確資訊的投資分析工具。

In 1952, Markowitz proposed the Mean-variance model (MV-model) without considering short selling. Therefore, most researches have focused only on the effect of long position but paid less attention on the behavior of short selling. To cope with the short selling issue, this research proposes four models based on MV-model which releases the limitation of short selling. First, short selling is incorporated into the MV-model. However, short selling is a good hedging tool but with high variance. Thus the number of short selling in the portfolio selection is minimized. Second, under considering the short selling in the portfolio selection, the minimization of proportion of short selling is further considered in the model. Third, in order to eliminate the trade-off between return and risk, the concept of De Novo programming is applied in the portfolio selection model. Hence, the proposed portfolio would show the least budget needed to achieve these two goals at once. Fourth, return, risk, number of sold short, and number of total selected securities are viewed as four criteria to be optimized through multiple objective programming. Two data sets are tested to verify these four models which can choose a portfolio selection effectively under considering short selling.

摘要 Ⅰ
Abstract Ⅱ
Contents Ⅳ
List of Figures Ⅵ
List of Tables Ⅶ
List of Appendices Ⅷ
Chaper 1　Introduction 1
1.1　Background and Motivation 1
1.2　Organization of the Thesis 3
Chapter 2　Related Models 5
2.1　Mean-variance model 5
2.2　Short Selling 8
2.3　De Novo Programming 11
2.4　Multiple Criteria Optimization 18
Chapter 3 The Proposed Models 22
3.1　Minimization of Short Selling 22
3.2　Minimization of proportion of Short Selling 24
3.3　De Novo Programming for Portfolio Selection with Short Selling 26
3.4　Multiple Criteria Optimization for Portfolio Selection with Short Selling 27
Chapter 4　Examples 31
4.1　Model 1: Testing result by using data set 1 37
4.2　Model 1: Testing result by using data set 2 38
4.3　Model 2: Testing result by using data set 1 39
4.4　Model 2: Testing result by using data set 2 40
4.5　Model 3: Testing result by using data set 1 42
4.6　Model 3: Testing result by using data set 2 44
4.7　Model 4: Testing result by using data set 1 46
4.8　Model 4: Testing result by using data set 2 47
4.9　Complexity 49
Chapter 5　Conclusion and Future Research 51
5.1　Conclusion 51
5.2　Fututre Research 52
References 54
Appendix 57

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