This study investigates the performance of the weight optimization by
comparing the performance of the portfolios of fund of funds (FoF)
constructed by the Markowitz Mean-Variance (MV) model or Genetic
Algorithm (GA) to that of S&P 500 and that of equal weight portfolio of
Mutual funds. The chosen target funds are denominated in U.S. dollar or
euros, and are chosen from the European market, United European market,
Emerging market, Pacific market, South Asia market, Asia Pacific Zone
market, American market, and Global market. The study period started on
February 1, 1998 and ended on December 1, 2006. In this thesis, we test
whether the Genetic Algorithm can beat the traditional Markowitz Mean-
Variance model or not. At last, we get some results from empirical
evidence. First, the Genetic Algorithm model performs better than the
Markowitz Mean-Variance in performance measures of Sharpe, Treynor and
Jensen's alpha. Second, both the Markowitz Mean-Variance model and
Genetic Algorithm can beat the equal weight portfolios. Finally, the
Markowitz Mean-Variance model and the Genetic Algorithm are not better
than market index significantly.