{"title":"基于遗传算法优化技术交易规则的投资组合选择","authors":"J. F. Kotowski, E. Szlachcic, P. M. Wańtowski","doi":"10.1109/INES.2010.5483839","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a portfolio selection method based on a set of technical trading rules, which are optimized by a genetic algorithm. The aim of the research was to check if it is possible to obtain a set of trading rules deriving from technical indicators, which could be used to create a portfolio able to outperform standard portfolio models based upon Modern Portfolio Theory. On the contrary to the typical portfolio approach incorporating expected return and variance, presented method relies on market momentum analysis and stock timing using selected technical indicators.","PeriodicalId":118326,"journal":{"name":"2010 IEEE 14th International Conference on Intelligent Engineering Systems","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Portfolio selection based on technical trading rules optimized with a genetic algorithm\",\"authors\":\"J. F. Kotowski, E. Szlachcic, P. M. Wańtowski\",\"doi\":\"10.1109/INES.2010.5483839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a portfolio selection method based on a set of technical trading rules, which are optimized by a genetic algorithm. The aim of the research was to check if it is possible to obtain a set of trading rules deriving from technical indicators, which could be used to create a portfolio able to outperform standard portfolio models based upon Modern Portfolio Theory. On the contrary to the typical portfolio approach incorporating expected return and variance, presented method relies on market momentum analysis and stock timing using selected technical indicators.\",\"PeriodicalId\":118326,\"journal\":{\"name\":\"2010 IEEE 14th International Conference on Intelligent Engineering Systems\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE 14th International Conference on Intelligent Engineering Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INES.2010.5483839\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE 14th International Conference on Intelligent Engineering Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INES.2010.5483839","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Portfolio selection based on technical trading rules optimized with a genetic algorithm
In this paper, we propose a portfolio selection method based on a set of technical trading rules, which are optimized by a genetic algorithm. The aim of the research was to check if it is possible to obtain a set of trading rules deriving from technical indicators, which could be used to create a portfolio able to outperform standard portfolio models based upon Modern Portfolio Theory. On the contrary to the typical portfolio approach incorporating expected return and variance, presented method relies on market momentum analysis and stock timing using selected technical indicators.
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