Using Genetic Algorithm for Index Tracking–Evidence from Shanghai 50

Jian-he Liu (Zhejiang University of Finance and Economics)
Xin Wu (Zhejiang University of Finance and Economics)
Qing-Song Fang (Zhejiang University of Finance and Economics)

Indonesian Journal of Electrical Engineering and Computer Science
Vol 12, No 3: March 2014

This paper uses historical data of Shanghai 50 Index as sample data, replaces traditional optimization methods with genetic algorithm, uses clustering analysis method to build tracking portfolio, and compares the empirical results with those of traditional optimization methods. The empirical results of Shanghai 50 index show that using genetic algorithm for index tracking can get better performance with lower volatility. DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.4801