{"title":"The Agent-Based Hedge Fund","authors":"R. Barbosa, O. Belo","doi":"10.1109/WI-IAT.2010.149","DOIUrl":null,"url":null,"abstract":"In this article we describe the implementation of a diversified investment strategy using 25 intelligent agents. Each agent utilizes several data mining models and other artificial intelligence techniques to autonomously day trade an American stock. The agents were individually tested with out-of-sample data corresponding to the period between February of 2006 and June of 2010, and most achieved an acceptable performance. By integrating the 25 agents in a multi-agent system, we were able to obtain much better results (according to the return and maximum drawdown metrics); this leads us to believe that it might be possible to use one such system in the creation of a profitable hedge fund in which the investment decisions can be made without human intervention.","PeriodicalId":340211,"journal":{"name":"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WI-IAT.2010.149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In this article we describe the implementation of a diversified investment strategy using 25 intelligent agents. Each agent utilizes several data mining models and other artificial intelligence techniques to autonomously day trade an American stock. The agents were individually tested with out-of-sample data corresponding to the period between February of 2006 and June of 2010, and most achieved an acceptable performance. By integrating the 25 agents in a multi-agent system, we were able to obtain much better results (according to the return and maximum drawdown metrics); this leads us to believe that it might be possible to use one such system in the creation of a profitable hedge fund in which the investment decisions can be made without human intervention.