A Passive Portfolio Model- Mean Variance and Semi-variance
碩士 === 靜宜大學 === 資訊碩士在職專班 === 102 === Since researches have indicated that actively managed portfolios fail to beat the market, index investing, such as index funds and ETFs, which aim to track the market performance, and require few efforts on stock-picking and market-timing is more and more popular...
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ndltd-TW-102PU0013920022015-10-13T23:30:33Z http://ndltd.ncl.edu.tw/handle/33375689823555964298 A Passive Portfolio Model- Mean Variance and Semi-variance 使用均異模型及半變異數建立被動式投資組合 Yu-Chen Chen 陳佑賑 碩士 靜宜大學 資訊碩士在職專班 102 Since researches have indicated that actively managed portfolios fail to beat the market, index investing, such as index funds and ETFs, which aim to track the market performance, and require few efforts on stock-picking and market-timing is more and more popular among the investors. Index investing, which aims to track the benchmark index return, has been one of the most popular financial tools and the research topics among the academic and the practitioners. However, there have been few studies on the constructing an effective index portfolio. The problems for existing models are tremendous monitoring expenses as well as the downside risk issues. This study aims to address these two issues. We propose a new model that takes account of downside risk and the number of stocks. Huge stocks historical data are stored in a database and given meaning using our model. Stocks that possess the feature of effectiveness are chosen and then given weights based on the optimum theory. The results show that our proposed model provides a new way of constructing an index portfolio, which provides implications for both the academic and the practitioners. Jieh-Shan Yeh Liang-Chuan Wu 葉介山 巫亮全 2014 學位論文 ; thesis 49 zh-TW |
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碩士 === 靜宜大學 === 資訊碩士在職專班 === 102 === Since researches have indicated that actively managed portfolios fail to beat the market, index investing, such as index funds and ETFs, which aim to track the market performance, and require few efforts on stock-picking and market-timing is more and more popular among the investors. Index investing, which aims to track the benchmark index return, has been one of the most popular financial tools and the research topics among the academic and the practitioners. However, there have been few studies on the constructing an effective index portfolio. The problems for existing models are tremendous monitoring expenses as well as the downside risk issues.
This study aims to address these two issues. We propose a new model that takes account of downside risk and the number of stocks. Huge stocks historical data are stored in a database and given meaning using our model. Stocks that possess the feature of effectiveness are chosen and then given weights based on the optimum theory. The results show that our proposed model provides a new way of constructing an index portfolio, which provides implications for both the academic and the practitioners.
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Jieh-Shan Yeh |
author_facet |
Jieh-Shan Yeh Yu-Chen Chen 陳佑賑 |
author |
Yu-Chen Chen 陳佑賑 |
spellingShingle |
Yu-Chen Chen 陳佑賑 A Passive Portfolio Model- Mean Variance and Semi-variance |
author_sort |
Yu-Chen Chen |
title |
A Passive Portfolio Model- Mean Variance and Semi-variance |
title_short |
A Passive Portfolio Model- Mean Variance and Semi-variance |
title_full |
A Passive Portfolio Model- Mean Variance and Semi-variance |
title_fullStr |
A Passive Portfolio Model- Mean Variance and Semi-variance |
title_full_unstemmed |
A Passive Portfolio Model- Mean Variance and Semi-variance |
title_sort |
passive portfolio model- mean variance and semi-variance |
publishDate |
2014 |
url |
http://ndltd.ncl.edu.tw/handle/33375689823555964298 |
work_keys_str_mv |
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