Title :
Multi-objective Portfolio Optimization Based on Fuzzy Genetic Algorithm
Author :
Huilin Yi ; Jianhui Yang
Author_Institution :
Sch. of Bus. Adm., South China Univ. of Technol., Guangzhou, China
Abstract :
Based on the Markowitz portfolio model, this paper considered the liquidity of the risk assets, set the minimum expected return rate of investors, and changed the inequality constraint to semi-gradient fuzzy number. Then used the penalty factor to adjust the objective function, taking the maximum liquidity and minimum risk of portfolio as the objectives, we established the Multi-objective portfolio optimization model. Using the weekly return rate and weekly turnover rate data of eight stocks that are typical in several industries, we can get the Pareto optimal solution set of risk assets investment proportion by fuzzy genetic algorithm. Investors can accord to the personal attitude toward return, risk, liquidity to choose better investment combination proportion of risk assets.
Keywords :
Pareto optimisation; fuzzy set theory; genetic algorithms; investment; risk analysis; stock markets; Markowitz portfolio model; Pareto optimal solution set; fuzzy genetic algorithm; inequality constraint; investment combination proportion; maximum liquidity; minimum expected investor return rate; minimum portfolio risk; multiobjective portfolio optimization model; penalty factor; risk asset investment proportion; risk asset liquidity; semigradient fuzzy number; stocks; weekly return rate; weekly turnover rate; Genetic algorithms; Investment; Linear programming; Mathematical model; Optimization; Portfolios; Security; Fuzzy genetic algorithm; Multi-objective; Pareto Optimality; Risk appetite;
Conference_Titel :
Computational Intelligence and Security (CIS), 2013 9th International Conference on
Conference_Location :
Leshan
Print_ISBN :
978-1-4799-2548-3
DOI :
10.1109/CIS.2013.26