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  • 學位論文

MV 及 MCVaR 投資組合模型之績效評估-大中華區股市之實證研究

Evaluation of the Performance in MV and MCVaR Models-An Empirical Study on Greater Chinese Stock Markets

指導教授 : 李沃牆

摘要


本研究運用平均數ー變異數模型(Mean-Variance Model)以及平均數ー條件風險值模型(Mean-CVaR Model)兩個模型,分別以台灣50指數成分股、香港恒生指數成分股、中國滬深300指數成分股,建立投資組合,找出最適權重與資產配置,再衡量最適之資產配置的績效。結果發現不同地區的選股呈現出不同的差異性存在;台灣M-CVaR模型權重變化有較集中趨勢,M-V模型則較分散;香港兩個模型皆為集中趨勢;中國則兩個模型之權重變化皆較分散。 應用幾何平均數、算術平均數、累積報酬率、Sharpe Ratio、Treynor Ratio、Jensen’s Alpha 以及Information Ratio比較不同時間、不同地區、不同標的投資績效。當信賴水準95%時,M-CVaR模型優於M-V模型;當信賴水準99%時,實證結果並無一致性。但若觀察所有的投資地區,由報酬率獲勝的次數或累積報酬率之比較次數可知,當信賴水準95%時,M-CVaR模型優於M-V模型,但M-CVaR或M-V模型是否優於指數表現則不一定。若從三個投資地區績效之合計次數選擇模型,則當信賴水準95%時,M-CVaR模型優於M-V模型且M-CVaR模型也勝過市場指標指數表現。 透過成對母體平均數差異t檢定的方式檢定兩個模型建構之投資組合在不同投資地區下之平均報酬率是否存在顯著差異?統計檢定結果顯示,不同選股地區之績效,僅在採用台灣投資時之平均報酬率與基準指數相比具有顯著的差異。 透過研究結果,提供投資人進行投資組合之建議,若投資人欲投資台灣,建議採用M-CVaR信賴水準99%模型;若欲投資中國或香港則建議採用參與指數之方式投資。

並列摘要


The study applies the Mean-Variance Model and Mean-CVaR to construct optimal weighted portfolios comprising stocks used in the TSEC Taiwan 50 Index, Hong Kong’s Hang Seng Index, and China’s CSI 300 Index. The purpose of this paper is to review the performance portfolios and find the optimal weights. The stock selection strategies in different regions showing a significant difference between Taiwan, Hong Kong and China. Geometric mean, arithmetic mean, Cumulative Return, Sharpe Ratio, Treynor Ratio, Jensen's Alpha and the Information Ratio are used to review the performance portfolios in different regions. When the confidence level of 95%, M-CVaR model is superior to M-V model; when the 99% confidence level, the empirical results were inconsistent. However, if observed in all investment regions, the number of wins by the rate of return or cumulative number of comparisons shows that the rate of return, when the confidence level of 95%, M-CVaR model is superior to M-V model, but the M-CVaR or the MV model is superior Index performance is not necessarily. If the performance from three of the total number of investment strategy choice model, when the confidence level of 95%, M-CVaR model is superior to M-V model and M-CVaR model is also better than the market benchmark index performance. By investigating the average divergence with t-test, we analyzed whether or not the average return showed statistical significance between these two models. The results revealed that the performance of different investment strategies only evinced statistical significance from the benchmark index in the case of the average return on investment in Taiwan stocks. In conculsion, our investigation provide investors with recommendations for their investment portfolios. If investors wish to invest in Taiwan, it is recommended that they use the M-CVaR model with a confidence level of 99%. If investment in China or Hong Kong stocks is desired, choosing an index-bound approach will be appropriate.

參考文獻


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被引用紀錄


方俐潔(2017)。投資組合績效導入金融科技的機器人理財-以台灣股票市場為例〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2017.00185
陳怡君(2014)。外匯投資組合績效與風險評估〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2014.00951

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