A hybrid of adaptive genetic algorithm and pattern search for stock index optimized replicate

Author

Chen, Gaobo ; Chen, Xiufang

Author_Institution

Dept. of Math. & Phys., Wuhan Polytech. Univ., Wuhan, China

fYear

2011

fDate

8-10 Aug. 2011

Firstpage

4912

Lastpage

4915

Abstract

How to allocate the weights of stocks is an interesting technology in stock index optimized replicate. This paper proposed a hybrid algorithm of adaptive genetic algorithm and pattern search (AGA-PS) to find the optimal portfolio weights. In AGA-PS, the crossover probability and mutation probability are adjusted adaptively. The weight from adaptive genetic algorithm is as the search start point of pattern search. The experiment result of AGA-PS, which has smaller tracking error compared with GA and AGA, has shown that AGA-PS model is feasible and effective to the stock portfolio.

Keywords

genetic algorithms; investment; probability; search problems; AGA-PS; adaptive genetic algorithm; crossover probability; index investment purchases; mutation probability; optimal portfolio weights; pattern search; search start point; stock index optimized replicate; stock portfolio; Adaptation models; Biological cells; Genetic algorithms; Indexes; Investments; Optimization; Portfolios; adaptive genetic algorithm; index optimized replicate; pattern search; portfolio; stock;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on

Conference_Location

Deng Leng

Print_ISBN

978-1-4577-0535-9

Type

conf

DOI

10.1109/AIMSEC.2011.6011104

Filename

6011104