In this thesis, we propose an investment strategy for the world mutual funds. We first define the global trend indicator (GTI) for evaluating the price change trend of the funds in the future. Then, based on GTI, we derive the monitoring indicator (MI) to measure whether the fund market is in the bull or bear state. MI decides the buying or selling signal. The goodness of a fund is determined by some weighted combination of short-term performance and long-term performance. The weights of various performances are decided by the genetic algorithm, which can dynamically adjusted with priorities of interested funds according to their past performances (profitability). When a buying signal is triggered by MI, the funds with high performance are more likely to be picked than those with low performance. In our experimental results from January 1999 to December 2008 (10 years in total), we achieve the annual profit higher than 10%, which is a significant improvement to other existing methods.

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