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Position building in competition is a game with incomplete information

Position building in competition is a game with incomplete information ArXiv ID: 2501.01241 “View on arXiv” Authors: Unknown Abstract This paper examines strategic trading under incomplete information, where firms lack full knowledge of key aspects of their competitors’ trading strategies such as target sizes and market impact models. We extend previous work on competitive trading equilibria by incorporating uncertainty through the framework of Bayesian games. This allows us to analyze scenarios where firms have diverse beliefs about market conditions and each other’s strategies. We derive optimal trading strategies in this setting and demonstrate how uncertainty significantly impacts these strategies compared to the complete information case. Furthermore, we introduce a novel approach to model the presence of non-strategic traders, even when strategic firms disagree on their characteristics. Our analysis reveals the complex interplay of beliefs and strategic adjustments required in such an environment. Finally, we discuss limitations of the current model, including the reliance on linear market impact and the lack of dynamic strategy adjustments, outlining directions for future research. ...

January 2, 2025 · 2 min · Research Team

Trading Large Orders in the Presence of Multiple High-Frequency Anticipatory Traders

Trading Large Orders in the Presence of Multiple High-Frequency Anticipatory Traders ArXiv ID: 2403.08202 “View on arXiv” Authors: Unknown Abstract We investigate a market with a normal-speed informed trader (IT) who may employ mixed strategy and multiple anticipatory high-frequency traders (HFTs) who are under different inventory pressures, in a three-period Kyle’s model. The pure- and mixed-strategy equilibria are considered and the results provide recommendations for IT’s randomization strategy with different numbers of HFTs. Some surprising results about investors’ profits arise: the improvement of anticipatory traders’ speed or a more precise prediction may harm themselves but help IT. ...

March 13, 2024 · 2 min · Research Team