Game Theory for Predicting Stocks’ Closing Prices

João Costa Freitas (), Alberto Adrego Pinto () and Óscar Felgueiras ()
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João Costa Freitas: Faculty of Sciences, University of Porto, R Campo Alegre, 4169-007 Porto, Portugal
Alberto Adrego Pinto: Faculty of Sciences, University of Porto, R Campo Alegre, 4169-007 Porto, Portugal
Óscar Felgueiras: Faculty of Sciences, University of Porto, R Campo Alegre, 4169-007 Porto, Portugal

Mathematics, 2024, vol. 12, issue 17, 1-49

Abstract: We model the financial markets as a game and make predictions using Markov chain estimators. We extract the possible patterns displayed by the financial markets, define a game where one of the players is the speculator, whose strategies depend on his/her risk-to-reward preferences, and the market is the other player, whose strategies are the previously observed patterns. Then, we estimate the market’s mixed probabilities by defining Markov chains and utilizing its transition matrices. Afterwards, we use these probabilities to determine which is the optimal strategy for the speculator. Finally, we apply these models to real-time market data to determine its feasibility. From this, we obtained a model for the financial markets that has a good performance in terms of accuracy and profitability.

Keywords: financial markets; games against nature; Markov chains (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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