英文摘要 |
Since Markowitz proposed mean-variance portfolio model in 1952, portfolio optimization, based on an efficient frontier, has continuously been discussed. Normally, the portfolios on the efficient frontier show a positive correlation between risk and return. Higher returns are always companied with higher risks, and vise versa. It leads to a dilemma for investors to make their decisions. And moreover, when there are too many securities or asset classes in the pool, it's difficult to obtain a precise solution under some limit of time. This research applies artificial intelligence to offer a rational and convenient solution on portfolio optimization. Besides, this research compares a few models by analyzing the performances under different level of over-reaction and size of investing capitals. The results reflect the characteristics and the pros and cons of the models in more realized circumstances. It provides a good reference for portfolio building. The result of this research shows that over-reaction appears in most models. And the performances are quite different according to different capital levels. So we provide a dynamic invest line to express the optimization-portfolio model in the different capital levels. |