The YTM-based stock portfolio mining approach by genetic algorithm

GrC(2013)

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摘要
This study proposes a yield-to-maturity (YTM)-based genetic portfolio selection model with user defined constraints, namely YTMGPSM. A set of real numbers are encoded into a chromosome to form a possible portfolio, which presents whether buy or not buy and purchased units of assets. The fitness value of a chromosome is evaluated by return on investment, value at risk and suitability of the respective portfolio. The suitability of a chromosome consists of portfolio penalty and investment capital penalty that are used to reflect the satisfactions of user predefined maximum investment and maximum number of companies, respectively. Experiments on real dataset are made to show the merits of the proposed approach.
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关键词
cost-benefit analysis,m-v model,ytm-based stock portfolio mining,portfolio selection,investment capital penalty,chromosome,yield to maturity,return on investment,genetic algorithm,genetic algorithms,yield-to-maturity,investment,transaction lots,ytmgpsm,portfolio penalty,cost benefit analysis
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