英文摘要 |
The main purpose of this study is to use the concept of collective intelligence to dynamically determine the optimal ratio of capital investment through the multiple-gene design of gene expression programming (GEP), and the weighting mechanism of GEP random numeric constants (RNC), hoping that the investment behavior to avoid been affected by human factors and obtain stable ROI..The results of studies show that: (1)The more stringent the trading signals are the worse it functions. 70-30 are more likely to bring stable excess returns for investors. (2) The model proposed in this study does have a good opportunity to bring acceptable rewards for investors. But it cannot function as sell as it is supposed in the event that unexpected economy data out of expectation are announced. (3) Among the nine technical indicators used in this study, KD and RSI are more likely to bring excess returns for the model according to the evolution of GEP, while MA, MACD, and Bollinger bands have less value for reference. |