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Information Journal Paper

Title

THE COMPARISON OF GENETIC AND WEED ALGORITHMS IN PORTFOLIO OPTIMIZATION

Pages

  77-84

Abstract

 In this paper, Genetic and weed algorithms ARe used to solve constrained mean-semi variance portfolio problem. Then AR model and simple average ARe compared to predict expected return of stocks.23 active stocks from June 22, 2014 to June 21, 2016 ARe used as our sample. The results indicate that, weed algorithm despite its longer time consuming has better performance than Genetic algorithm. And AR (2) model has more accurate prediction than simple average in predicting expected rate of return. Finally, we compare expected and real efficient frontier, the results indicate that, in lower risk, AR model has better prediction accuracy. So in that ARea, we can allocate our asset with higher certainty.

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  • Cite

    APA: Copy

    FESHARI, MAJID, & MAZAHERIFAR, POORIA. (2018). THE COMPARISON OF GENETIC AND WEED ALGORITHMS IN PORTFOLIO OPTIMIZATION. FINANCIAL KNOWLEDGE OF SECURITY ANALYSIS (FINANCIAL STUDIES), 11(38 ), 77-84. SID. https://sid.ir/paper/200273/en

    Vancouver: Copy

    FESHARI MAJID, MAZAHERIFAR POORIA. THE COMPARISON OF GENETIC AND WEED ALGORITHMS IN PORTFOLIO OPTIMIZATION. FINANCIAL KNOWLEDGE OF SECURITY ANALYSIS (FINANCIAL STUDIES)[Internet]. 2018;11(38 ):77-84. Available from: https://sid.ir/paper/200273/en

    IEEE: Copy

    MAJID FESHARI, and POORIA MAZAHERIFAR, “THE COMPARISON OF GENETIC AND WEED ALGORITHMS IN PORTFOLIO OPTIMIZATION,” FINANCIAL KNOWLEDGE OF SECURITY ANALYSIS (FINANCIAL STUDIES), vol. 11, no. 38 , pp. 77–84, 2018, [Online]. Available: https://sid.ir/paper/200273/en

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