Risk Measurements on Online Portfolio Selection
碩士 === 靜宜大學 === 財務工程學系 === 107 === This paper attempts to the Value at Risk (VaR) of online portfolios. The online portfolio includes Buy and Hold, Best Stock, Constant Rebalance Portfolio, Follow the Winner and Follow the Loser, the investment sample is fifty Exchange Traded Funds (ETF), using the...
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ndltd-TW-107PU0003050072019-10-10T03:35:36Z http://ndltd.ncl.edu.tw/handle/fhe978 Risk Measurements on Online Portfolio Selection 線上投資策略的風險測量 HUANG, JING-YA 黃靖雅 碩士 靜宜大學 財務工程學系 107 This paper attempts to the Value at Risk (VaR) of online portfolios. The online portfolio includes Buy and Hold, Best Stock, Constant Rebalance Portfolio, Follow the Winner and Follow the Loser, the investment sample is fifty Exchange Traded Funds (ETF), using the variance-covariance method to calculate the Value at Risk, and comparing the risk of the wealth of different investment methods. Verify that the portfolio is effective in controlling the risk loss of the Exchange Traded Funds. The empirical results show that the return rate of the Exchange Traded Funds portfolio is less than the Value at Risk of the portfolio, and the loss representing the portfolio is controlled by the maximum loss calculated by the Value at Risk. It is proved that the method of the portfolio risk value is quite reliable. In the measured results, it is found that in the Best stock strategy and Follower Loser strategy, the portfolio approach is not completely less than the maximum loss of the ETF's Value at Risk, which means that using these three portfolios has the opportunity to increase the risk, but Buy and Hold, Constant Rebalance Portfolio, Follow the winner's UP strategy and the EG strategy, these four portfolio approaches can completely reduce and control the maximum loss of the Exchange Traded Funds. CHANG, CHIEN-HUNG 張建鴻 2019 學位論文 ; thesis 71 zh-TW |
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碩士 === 靜宜大學 === 財務工程學系 === 107 === This paper attempts to the Value at Risk (VaR) of online portfolios. The online portfolio includes Buy and Hold, Best Stock, Constant Rebalance Portfolio, Follow the Winner and Follow the Loser, the investment sample is fifty Exchange Traded Funds (ETF), using the variance-covariance method to calculate the Value at Risk, and comparing the risk of the wealth of different investment methods. Verify that the portfolio is effective in controlling the risk loss of the Exchange Traded Funds. The empirical results show that the return rate of the Exchange Traded Funds portfolio is less than the Value at Risk of the portfolio, and the loss representing the portfolio is controlled by the maximum loss calculated by the Value at Risk. It is proved that the method of the portfolio risk value is quite reliable. In the measured results, it is found that in the Best stock strategy and Follower Loser strategy, the portfolio approach is not completely less than the maximum loss of the ETF's Value at Risk, which means that using these three portfolios has the opportunity to increase the risk, but Buy and Hold, Constant Rebalance Portfolio, Follow the winner's UP strategy and the EG strategy, these four portfolio approaches can completely reduce and control the maximum loss of the Exchange Traded Funds.
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author2 |
CHANG, CHIEN-HUNG |
author_facet |
CHANG, CHIEN-HUNG HUANG, JING-YA 黃靖雅 |
author |
HUANG, JING-YA 黃靖雅 |
spellingShingle |
HUANG, JING-YA 黃靖雅 Risk Measurements on Online Portfolio Selection |
author_sort |
HUANG, JING-YA |
title |
Risk Measurements on Online Portfolio Selection |
title_short |
Risk Measurements on Online Portfolio Selection |
title_full |
Risk Measurements on Online Portfolio Selection |
title_fullStr |
Risk Measurements on Online Portfolio Selection |
title_full_unstemmed |
Risk Measurements on Online Portfolio Selection |
title_sort |
risk measurements on online portfolio selection |
publishDate |
2019 |
url |
http://ndltd.ncl.edu.tw/handle/fhe978 |
work_keys_str_mv |
AT huangjingya riskmeasurementsononlineportfolioselection AT huángjìngyǎ riskmeasurementsononlineportfolioselection AT huangjingya xiànshàngtóuzīcèlüèdefēngxiǎncèliàng AT huángjìngyǎ xiànshàngtóuzīcèlüèdefēngxiǎncèliàng |
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1719263512720572416 |