MFGTApr 3

When cooperation is beneficial to all agents

arXiv:2604.0286229.6h-index: 24
Predicted impact top 70% in MF · last 90 daysOriginality Incremental advance
AI Analysis

This work addresses theoretical market efficiency and individual rationality, providing a foundational condition for beneficial cooperation, but it is incremental as it builds on existing semimartingale frameworks.

The paper tackles the problem of when cooperation among agents in a market can strictly improve each agent's utility, deriving a necessary and sufficient condition based on preferences and pricing measures within a semimartingale framework.

Within a general semimartingale framework, we study the relationship between collective market efficiency and individual rationality. We derive a necessary and sufficient condition for the existence of (possibly zero-sum) exchanges among agents that strictly increase their indirect utilities and characterize this condition in terms of the compatibility between agents' preferences and collective pricing measures. The framework applies to both continuous- and discrete-time models and clarifies when cooperation leads to a strict improvement in each participating agent's indirect utility.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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