{"title":"Uczenie maszynowe w budowie portfela inwestycyjnego","authors":"Przemysław Grobelny, T. Kaczmarek, M. Piotrowski","doi":"10.18559/978-83-8211-083-8/9","DOIUrl":null,"url":null,"abstract":"The chapter describes the characteristics of machine learning methods in their possible application in investment portfolio optimization. With the use of the SWOT analysis, the features of the algorithms responsible for their increasing popularization in the formulation of investment strategies and their limitations in this regard were discussed. The prospects for further development of machine learning were described in the context of the market and technological environment. In addition, based on the review of the research, the possibilities of using machine learning algorithms in managing the investment portfolio and the use of modern research methods, which can be a creative development of the needs and solution to the problems faced by researchers of financial science and financial market practitioners, have been presented.","PeriodicalId":110813,"journal":{"name":"Innowacje finansowe w gospodarce 4.0","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Innowacje finansowe w gospodarce 4.0","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18559/978-83-8211-083-8/9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Uczenie maszynowe w budowie portfela inwestycyjnego
The chapter describes the characteristics of machine learning methods in their possible application in investment portfolio optimization. With the use of the SWOT analysis, the features of the algorithms responsible for their increasing popularization in the formulation of investment strategies and their limitations in this regard were discussed. The prospects for further development of machine learning were described in the context of the market and technological environment. In addition, based on the review of the research, the possibilities of using machine learning algorithms in managing the investment portfolio and the use of modern research methods, which can be a creative development of the needs and solution to the problems faced by researchers of financial science and financial market practitioners, have been presented.