碩士 / 南華管理學院 / 亞洲太平洋研究所 / 87 / Artificial neural network method is used in the paper to forecast of Shanghai and Shenzhen B shares. The forecast period used in this research is from October 1997 to December 1998. A stepwise regression is chosen to compare with the result of the correlation method and neural network method. In our research, investment return rate is used to measure performance on neural network model and multiple regression model.
The result of our finding is as follows:
1、The comparison of investment return rates on buy-and-sell hold strategy between artificial neural network and multiple regression have proof the ability to predict.
2、As far as the direction of the stock will go, multiple regression have a better result than neural network. For measure the variability of the stock, the artificial neural network has better result than the multiple regression.
3、When the artificial neural network is used on the conservative mode have shown better investment return rate than the active mode.
4、For choosing variables the stepwise regression shown have better result on the Shanghai B shares. On Shenzhen B shares correlation method have shown better result than stepwise regression. In our model it have shown a relationship between the methods of choosing variables and the model used to forecast stock.
In our conclusion we find the artificial neural network has learning ability which allow to improve the model performance than multiple regression. Our research is only serve as pioneer study to understand the neural network model and stock market on Shenzhen B shares and Shanghai B shares. A more extensive information and study is needed in the future research.
| Identifer | oai:union.ndltd.org:TW/087NHMC0664006 |
| Creators | Jen-Kuei Wang, 王仁癸 |
| Contributors | Helen Wang, 連輕盈 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 73 |
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