Application of Genetic Algorithms in Stock Market Simulation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F12%3A50000214" target="_blank" >RIV/62690094:18450/12:50000214 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.sbspro.2012.06.619" target="_blank" >http://dx.doi.org/10.1016/j.sbspro.2012.06.619</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.sbspro.2012.06.619" target="_blank" >10.1016/j.sbspro.2012.06.619</a>

Result language
angličtina
Original language name
Application of Genetic Algorithms in Stock Market Simulation
Original language description
Development of stock market is affected by many factors. It is difficult to predict changes in prices of stocks because of many parameters in behavioral algorithms. There is also problem with learning soft-skills because of many variables. Application ofgenetic algorithms can help find suitable pre-set of behavioral patterns, functions and its parameters. In this paper we describe creation and implementation genetic algorithms to existing multi-agent simulation. This existing simulation provides basicmodel of simulation of stock market members behavior. The main goal of this article is describe how to implement genetic algorithm into this type of simulation. The main advantage of using genetic algorithms is dynamically created decision process or function of each agent. Article describes process of creating decision, simulating behavior of agents which decision algorithm was created by genetic programming. Next point is to show, how can be this implementation of genetic algorithms us
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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