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Title:Mehanski trgovalni sistem na osnovi spodbujevanega učenja : na študijskem programu 2. stopnje Matematika
Authors:ID Drevenšek, Anja (Author)
ID Jagrič, Timotej (Mentor) More about this mentor... New window
ID Jakovac, Marko (Comentor)
Files:.pdf MAG_Drevensek_Anja_2023.pdf (2,33 MB)
MD5: D4B67CE6DF71E535935207C42DB7C1EC
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FNM - Faculty of Natural Sciences and Mathematics
Abstract:Umetna inteligenca in strojno učenje postajata del našega vsakdana. Tako je tudi na finančnih trgih, kjer t. i. inteligentni agenti trgujejo z vrednostnimi papirji. V magistrskem delu je obravnavan primer takšnega mehanskega trgovalnega sistema za trgovanje z delnicami. Model temelji na spodbujevanem učenju in uporablja realne prosto dostopne borzne podatke. V prvem delu so preučeni temeljni pojmi verjetnosti in umetne nevronske mreže. Nadalje je podrobneje opredeljeno spodbujevano učenje in matematično ozadje spodbujevanega učenja. Drugi del magistrske naloge predstavlja implementiran model mehanskega trgovalnega sistema. Zastavljeni in učeni so štirje agenti, ki se med seboj razlikujejo po sistemu nagrajevanja. Agenti so testirani in primerjani s pasivno strategijo ter med seboj.
Keywords:strojno učenje, spodbujevano učenje, umetne nevronske mreže, inteligentni agent, trgovanje z vrednostnimi papirji.
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[A. Drevenšek]
Year of publishing:2023
Number of pages:VIII, 67 f.
PID:20.500.12556/DKUM-84569 New window
UDC:519.22:368.029(043.2)
COBISS.SI-ID:157804035 New window
Publication date in DKUM:05.07.2023
Views:478
Downloads:76
Metadata:XML DC-XML DC-RDF
Categories:FNM
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:21.06.2023

Secondary language

Language:English
Title:Mechanical trading system based on reinforcement learning : magistrsko delo
Abstract:Artificial intelligence and machine learning are becoming part of our everyday life. The situation is similar in financial markets, where so-called intelligent agents trade securities. In this Master's thesis an example of such a mechanical trading system for stock trading is discussed. The model is based on reinforcement learning and uses real, freely available stock market data. In the first part of the thesis, the basic concepts of probability and artificial neural networks are studied. Further, the reinforcement learning and the mathematical background of reinforcement learning are defined in more detail. The second part of the Master’s thesis presents the implemented model of the mechanical trading system. Four intelligent agents, which differ in terms of reward systems, are presented and tested. The agents are tested and compared, using a passive strategy.
Keywords:machine learning, reinforcement learning, artificial neural network, intelligent agent, trading financial instruments.


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