论文信息 - Genetic algorithms for the investment of the mutual fund with global trend indicator

Genetic algorithms for the investment of the mutual fund with global trend indicator

Our investment strategy for the world mutual funds can be divided into three main parts. First, the global trend indicator (GTI) is defined 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. Finally, to decide the signal for buying or selling funds, a genetic algorithm is invoked to dynamically select funds according to their past performances (profitability). In our experimental results from January 1999 to December 2008 (10years in total), we achieve the annual profit higher than 10%.

[1] Ping-Feng Pai,et al. A hybrid ARIMA and support vector machines model in stock price forecasting , 2005 .

[2] Wu Meng,et al. Application of Support Vector Machines in Financial Time Series Forecasting , 2007 .

[3] Masayuki Yamamura,et al. Genetic algorithm with search area adaptation for the function optimization and its experimental analysis , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[4] Shouyang Wang,et al. Forecasting stock market movement direction with support vector machine , 2005, Comput. Oper. Res..

[5] Ingoo Han,et al. Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index , 2000 .

[6] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[7] Theodore B. Trafalis,et al. Short term forecasting with support vector machines and application to stock price prediction , 2008, Int. J. Gen. Syst..

[8] Hiok Chai Quek,et al. Brain-inspired genetic complementary learning for stock market prediction , 2005, 2005 IEEE Congress on Evolutionary Computation.