A Game-theoretic model of forex trading with stochastic strategies and information asymmetry
Patrick Naivasha (1), George Musumba (1), Patrick Gikunda (1), John, Wandeto (1) ((1) Dedan Kimathi University of Technology)

TL;DR
This paper develops a game-theoretic model of forex trading that incorporates stochastic strategies and information asymmetry, revealing how market advantage can lead to consistent trader losses and informing better predictive analytics.
Contribution
It introduces a novel game-theoretic framework modeling market and trader interactions under imperfect information, highlighting the impact of informational advantage.
Findings
Market outperforms traders due to information asymmetry
Simulations show traders consistently lose against the market
Model suggests real-world forex favors well-informed market structures
Abstract
Interaction strategies for reward in competitive environments are significantly influenced by the nature and extent of available information. In financial markets, particularly foreign exchange (forex), traders operate independently with limited information, often yielding highly unpredictable outcomes. This study introduces a game-theoretic framework modeling the market as a strategically active participant, rather than a neutral entity, within a stochastic, imperfect information setting. In this model, the market alternates sequentially with new traders, each trader having limited visibility of the market's moves, while the market observes and counteracts each trader strategy. Through a series of simulations, we show that this information asymmetry enables the market to consistently outperform traders on aggregate. This outcome suggests that real-world forex environments may…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComplex Systems and Time Series Analysis · Stochastic processes and financial applications
