An Application of Grey Fourier Model on the Portfolio Selection Strategy and Spread Trading in Taiwan 50

碩士 === 國立臺灣科技大學 === 資訊管理系 === 97 === Investors have long faced the dilemma between higher returns and higher risks while trading in the stock market. To solve this problem, there are lots of researches emphasize on diversification of risks by constructing portfolios. This research focuses on applyin...

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Main Authors: Szu-hsien Yu, 余思嫺
Other Authors: Shang-wu Yu
Format: Others
Language:zh-TW
Published: 2009
Online Access:http://ndltd.ncl.edu.tw/handle/06745191380089404623
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spelling ndltd-TW-097NTUS53960412016-05-02T04:11:35Z http://ndltd.ncl.edu.tw/handle/06745191380089404623 An Application of Grey Fourier Model on the Portfolio Selection Strategy and Spread Trading in Taiwan 50 應用灰預測傅利葉殘差修正模型於台灣50現貨之投資組合策略及價差交易 Szu-hsien Yu 余思嫺 碩士 國立臺灣科技大學 資訊管理系 97 Investors have long faced the dilemma between higher returns and higher risks while trading in the stock market. To solve this problem, there are lots of researches emphasize on diversification of risks by constructing portfolios. This research focuses on applying the artificial intelligence tool to the portfolio selection strategy and spread trading, using the data of Taiwan 50 during April 2005 to March 2008. We use the new stock selection index to construct a portfolio to do the trading empirical study and find out the below conclusion: 1. In the aspect of stock return forecasting ability, using the Grey Fourier model gets better performance than using GM(1,1)model; and in the aspect of return volatility, using GM(1,1) gets better performance than GARCH(1,1) model. 2. According to the concept that the stock fluctuation will be effected by its direction of return and volatility, this research constructs a new stock selection index. We can construct a portfolio which has better performance than Taiwan 50 by this index. 3. In the timing strategy, using three signals of the same direction of return on investment can estimate the outcome of the next trading more correctly than using two signals. 4. In the period of this research, taking action or not on the timing strategy doesn’t make significant difference when we estimate there will be negative value of its return on investment. 5. When applying the portfolio constructed by the ranking first 26 stocks on the timing strategy of using three signals of positive return on investment value shows the best outcome. Shang-wu Yu 余尚武 2009 學位論文 ; thesis 60 zh-TW
collection NDLTD
language zh-TW
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description 碩士 === 國立臺灣科技大學 === 資訊管理系 === 97 === Investors have long faced the dilemma between higher returns and higher risks while trading in the stock market. To solve this problem, there are lots of researches emphasize on diversification of risks by constructing portfolios. This research focuses on applying the artificial intelligence tool to the portfolio selection strategy and spread trading, using the data of Taiwan 50 during April 2005 to March 2008. We use the new stock selection index to construct a portfolio to do the trading empirical study and find out the below conclusion: 1. In the aspect of stock return forecasting ability, using the Grey Fourier model gets better performance than using GM(1,1)model; and in the aspect of return volatility, using GM(1,1) gets better performance than GARCH(1,1) model. 2. According to the concept that the stock fluctuation will be effected by its direction of return and volatility, this research constructs a new stock selection index. We can construct a portfolio which has better performance than Taiwan 50 by this index. 3. In the timing strategy, using three signals of the same direction of return on investment can estimate the outcome of the next trading more correctly than using two signals. 4. In the period of this research, taking action or not on the timing strategy doesn’t make significant difference when we estimate there will be negative value of its return on investment. 5. When applying the portfolio constructed by the ranking first 26 stocks on the timing strategy of using three signals of positive return on investment value shows the best outcome.
author2 Shang-wu Yu
author_facet Shang-wu Yu
Szu-hsien Yu
余思嫺
author Szu-hsien Yu
余思嫺
spellingShingle Szu-hsien Yu
余思嫺
An Application of Grey Fourier Model on the Portfolio Selection Strategy and Spread Trading in Taiwan 50
author_sort Szu-hsien Yu
title An Application of Grey Fourier Model on the Portfolio Selection Strategy and Spread Trading in Taiwan 50
title_short An Application of Grey Fourier Model on the Portfolio Selection Strategy and Spread Trading in Taiwan 50
title_full An Application of Grey Fourier Model on the Portfolio Selection Strategy and Spread Trading in Taiwan 50
title_fullStr An Application of Grey Fourier Model on the Portfolio Selection Strategy and Spread Trading in Taiwan 50
title_full_unstemmed An Application of Grey Fourier Model on the Portfolio Selection Strategy and Spread Trading in Taiwan 50
title_sort application of grey fourier model on the portfolio selection strategy and spread trading in taiwan 50
publishDate 2009
url http://ndltd.ncl.edu.tw/handle/06745191380089404623
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