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

Authors:
Tsung-Jung Tsai;Chang-Biau Yang;Yung-Hsing Peng
Affiliations:
Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan;Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan;Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

Citing 1
Cited 1

Forecasting stock market movement direction with support vector machine

Computers and Operations Research

The trading on the mutual funds by gene expression programming with Sortino ratio

Applied Soft Computing

Quantified Score

Hi-index	12.05

Visualization

Abstract

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%.