MAMay 25

Recursive Multi-Agent Trading System: Iterative Optimized Portfolio Strategy Under Geopolitical Uncertainty

arXiv:2605.2531147.41 citations
Predicted impact top 53% in MA · last 90 daysOriginality Incremental advance
AI Analysis

For institutional investors, RMATS offers a risk-control-oriented architecture for capital preservation under geopolitical uncertainty.

RMATS, a recursive multi-agent trading system, achieves a maximum drawdown of 9.62% over 561 trading days across 24 assets, outperforming MVO (15.49%) and FinBERT (15.28%) in downside protection, though it underperforms in bull markets.

Recursive Multi-Agent Trading System (RMATS) integrates four specialized agents -- Sentiment, Report, Analysis, and Risk -- coordinated through a recursive Manager Agent with iterative feedback loops. Experimental evaluation over a 561-trading-day period (January 2023 to March 2025) across a 24-asset multi-class universe demonstrates that RMATS achieves a maximum drawdown of 9.62%, lower than MVO (15.49%) and FinBERT Sentiment (15.28%), and exhibits the lowest event-period drawdown in 3 of 5 geopolitical stress scenarios tested. While RMATS underperforms return-maximizing baselines in a sustained bull market environment, ablation studies confirm the individual contribution of each agent component to downside protection. These results position RMATS as a risk-control-oriented architecture suitable for institutions prioritizing capital preservation under geopolitical uncertainty.

Foundations

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

Your Notes