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Modelling Financial Markets via Multi-Agent Reinforcement Learning : How nothing interesting happened when I made AI trade with AI

Master-uppsats

Bocheński, Mikołaj

KTH/Skolan för elektroteknik och datavetenskap (EECS)

Publicerad: 2022

Språk: Engelska

Nyckelord

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⌕Deep Learning⌕Multi-agent system⌕Djupinlärning⌕Reinforcement Learning⌕Multi-agent systems⌕Förstärkningsinlärning⌕financial markets⌕finansiella marknader

Sammanfattning

The numerous previous attempts to simulate financial markets tended to be based on strong assumptions about markets or their participants. This thesis describes a more general kind of model - one in which deep reinforcement learning is used to train agents to make a profit while trading with each other on a virtual exchange. Such a model carries less inductive bias than most others - in theory, a neural network is capable of learning arbitrary decision rules. The model itself led to very simple results, but the conclusions from its construction will hopefully be of guidance to anyone implementing such a model in the future.

Information

Författare
Bocheński, Mikołaj
Lärosäte / institution
KTH/Skolan för elektroteknik och datavetenskap (EECS)
Publiceringsdatum
2022
Uppsatstyp
Master-uppsats
Språk
Engelska
Nyckelord
⌕Deep Learning⌕Multi-agent system⌕Djupinlärning⌕Reinforcement Learning⌕Multi-agent systems⌕Förstärkningsinlärning⌕financial markets⌕finansiella marknader

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