A Double-Stage Genetic Optimization Algorithm for Portfolio Selection

Autor:	Kin Keung Lai, Shouyang Wang, Lean Yu, Chengxiong Zhou
Rok vydání:	2006
Předmět:	Mathematical optimization Meta-optimization Artificial neural network Computer science Investment strategy Genetic algorithm Quality control and genetic algorithms Portfolio Asset allocation Project portfolio management Portfolio optimization
Zdroj:	Neural Information Processing ISBN: 9783540464846 ICONIP (3)
DOI:	10.1007/11893295_102
Popis:	In this study, a double-stage genetic optimization algorithm is proposed for portfolio selection. In the first stage, a genetic algorithm is used to identify good quality assets in terms of asset ranking. In the second stage, investment allocation in the selected good quality assets is optimized using a genetic algorithm based on Markowitz's theory. Through the two-stage genetic optimization process, an optimal portfolio can be determined. Experimental results reveal that the proposed double-stage genetic optimization algorithm for portfolio selection provides a very feasible and useful tool to assist the investors in planning their investment strategy and constructing their portfolio.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::66933e1ae8a9d3a7f28feec794faafd1 https://doi.org/10.1007/11893295_102 Zobrazit plný text záznamu