Open AccessThe Application of genetic algorithms for the selection of WSE companies in Warsaw for the investment portfolio.
Author(s) -
Beata Basiura,
Joanna Motyczyńska
Publication year - 2020
Publication title -
decision making in manufacturing and services
Language(s) - English
Resource type - Journals
eISSN - 2300-7087
pISSN - 1896-8325
DOI - 10.7494/dmms.2020.14.1.3809
Subject(s) - portfolio , post modern portfolio theory , modern portfolio theory , portfolio optimization , profit (economics) , application portfolio management , computer science , selection (genetic algorithm) , economics , context (archaeology) , operations research , replicating portfolio , mathematical optimization , econometrics , project portfolio management , financial economics , microeconomics , mathematics , machine learning , paleontology , management , project management , biology
Portfolio analysis is a tool particularly intended for investors. Risk assessment and risk specification make the investor able to properly diversify and offset the portfolio. Broadly speaking, there are multiple tools destined for building up an efficient set of portfolios.One of them is Markowitz’s model theory postulating building up a portfolio determined on the basis of equilibrium between expected profit level as well as accepted level of risk assessment.In the context of this paper, the objective is to shed some light on creating investment portfolios based on either Markowitz's portfolio theory or evolutionary algorithm. The simulation based methods for building up a portfolio of approximately 40-50 companies listed out in the primary marketof the Warsaw Stock Exchange using the selection function proposed in the BA thesis were presented.Portfolio profit values have been evaluated in a dynamically shifted time window. The conducted analysis showed shifts in the economy at certain periods of time. The implemented genetic algorithms smoothly handled the optimization with a relatively short processing time of the task result.