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Multi-objective Portfolio Optimization Based on Fuzzy Genetic Algorithm

Authors: Huilin Yi; Jianhui Yang;

Multi-objective Portfolio Optimization Based on Fuzzy Genetic Algorithm

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.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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