{"title":"外生影响下投资组合优化的遗传算法和MS求解器","authors":"Roshan Shaikh, A. Abbas","doi":"10.1109/ICCEE.2009.173","DOIUrl":null,"url":null,"abstract":"This study comprises of the Genetic Algorithm (GA) approach to optimize a constrained portfolio for maximum return with an acceptable risk for Karachi Stock Exchange (KSE) assets. The portfolio selection model used in this paper is based on the classical Markowitz mean-variance theory enhanced with exogenous influence of floor and ceiling. The results are compared with MS Excel Solver (Solver). It is found that the model works well under the influence of a high probability of local minima.","PeriodicalId":343870,"journal":{"name":"2009 Second International Conference on Computer and Electrical Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Genetic Algorithm and MS Solver for Portfolio Optimization under Exogenous Influence\",\"authors\":\"Roshan Shaikh, A. Abbas\",\"doi\":\"10.1109/ICCEE.2009.173\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study comprises of the Genetic Algorithm (GA) approach to optimize a constrained portfolio for maximum return with an acceptable risk for Karachi Stock Exchange (KSE) assets. The portfolio selection model used in this paper is based on the classical Markowitz mean-variance theory enhanced with exogenous influence of floor and ceiling. The results are compared with MS Excel Solver (Solver). It is found that the model works well under the influence of a high probability of local minima.\",\"PeriodicalId\":343870,\"journal\":{\"name\":\"2009 Second International Conference on Computer and Electrical Engineering\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Second International Conference on Computer and Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCEE.2009.173\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Second International Conference on Computer and Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCEE.2009.173","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Genetic Algorithm and MS Solver for Portfolio Optimization under Exogenous Influence
This study comprises of the Genetic Algorithm (GA) approach to optimize a constrained portfolio for maximum return with an acceptable risk for Karachi Stock Exchange (KSE) assets. The portfolio selection model used in this paper is based on the classical Markowitz mean-variance theory enhanced with exogenous influence of floor and ceiling. The results are compared with MS Excel Solver (Solver). It is found that the model works well under the influence of a high probability of local minima.
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