Applying Technical Indictors to Construct ETF Trading Strategy-An Application of Grey Relational and Neural Networks
碩士 === 南華大學 === 財務管理研究所 === 95 === This study applies the ETF stock price moving average to construct a profitable investment strategy. We first choose effective technical indicators by applying Grey relation analysis and then take the different combinations of technical indicators as input vecto...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2007
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| Online Access: | http://ndltd.ncl.edu.tw/handle/b3374x |
| Summary: | 碩士 === 南華大學 === 財務管理研究所 === 95 === This study applies the ETF stock price moving average to construct a profitable investment strategy. We first choose effective technical indicators by applying Grey relation analysis and then take the different combinations of technical indicators as input vector, the future ETF stock price moving average fluctuation as output vector to build an Artificial neural network forecast model. Furthermore, the investment performances of different trading strategies are compared. The results are as follows:
1.Choosing technical indicators by Grey relation analysis could effectively reduce forecasting bias.
2.The trading strategy derived by Artificial neural network shows a better performance than traditional six-day and twelve-day moving average crossover trading strategy and buy-and-hold strategy.
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