A Comparison of Portfolio Rebalancing Models by Using Different Risk Measurements

碩士 === 國立暨南國際大學 === 資訊管理學系 === 100 === With different risk measurement, the portfolio selection models including the Mean Variance model, the Mean Absolute Deviation model, the Downside Risk model, and Conditional Value at Risk model have been studied. Using the rolling window technique, multi-perio...

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Main Authors: Yang, Jianhong, 楊建宏
Other Authors: Yu Jingrung
Format: Others
Language:zh-TW
Published: 2012
Online Access:http://ndltd.ncl.edu.tw/handle/57938545254379865287
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spelling ndltd-TW-100NCNU03960412015-10-13T21:12:09Z http://ndltd.ncl.edu.tw/handle/57938545254379865287 A Comparison of Portfolio Rebalancing Models by Using Different Risk Measurements 不同風險衡量指標的投資組合再調整模型之比較 Yang, Jianhong 楊建宏 碩士 國立暨南國際大學 資訊管理學系 100 With different risk measurement, the portfolio selection models including the Mean Variance model, the Mean Absolute Deviation model, the Downside Risk model, and Conditional Value at Risk model have been studied. Using the rolling window technique, multi-period trading simulation is performed while short selling is also taken into account for these four models. Three kinds of performance assessments which are market value, expect return, and standard deviation are used to compare the performances among these four models. The Conditional Value at Risk model exhibits superior performance no matter whether we take the factor of short selling into account or not. According to the four models which are taken the factor of short selling into account, we observe that with the increased importance of the objective of short selling, it’s able not only to reduce the volatility of the portfolio risk but also increase the market value. Therefore, according to this study, we can infer that conditional value at risk measure of portfolio rebalancing model can exhibit superior performance in simulating the historical data of stocks which consists in Taiwan 50 index. Yu Jingrung 余菁蓉 2012 學位論文 ; thesis 66 zh-TW
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description 碩士 === 國立暨南國際大學 === 資訊管理學系 === 100 === With different risk measurement, the portfolio selection models including the Mean Variance model, the Mean Absolute Deviation model, the Downside Risk model, and Conditional Value at Risk model have been studied. Using the rolling window technique, multi-period trading simulation is performed while short selling is also taken into account for these four models. Three kinds of performance assessments which are market value, expect return, and standard deviation are used to compare the performances among these four models. The Conditional Value at Risk model exhibits superior performance no matter whether we take the factor of short selling into account or not. According to the four models which are taken the factor of short selling into account, we observe that with the increased importance of the objective of short selling, it’s able not only to reduce the volatility of the portfolio risk but also increase the market value. Therefore, according to this study, we can infer that conditional value at risk measure of portfolio rebalancing model can exhibit superior performance in simulating the historical data of stocks which consists in Taiwan 50 index.
author2 Yu Jingrung
author_facet Yu Jingrung
Yang, Jianhong
楊建宏
author Yang, Jianhong
楊建宏
spellingShingle Yang, Jianhong
楊建宏
A Comparison of Portfolio Rebalancing Models by Using Different Risk Measurements
author_sort Yang, Jianhong
title A Comparison of Portfolio Rebalancing Models by Using Different Risk Measurements
title_short A Comparison of Portfolio Rebalancing Models by Using Different Risk Measurements
title_full A Comparison of Portfolio Rebalancing Models by Using Different Risk Measurements
title_fullStr A Comparison of Portfolio Rebalancing Models by Using Different Risk Measurements
title_full_unstemmed A Comparison of Portfolio Rebalancing Models by Using Different Risk Measurements
title_sort comparison of portfolio rebalancing models by using different risk measurements
publishDate 2012
url http://ndltd.ncl.edu.tw/handle/57938545254379865287
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