Market-Dependent Communication in Multi-Agent Alpha Generation

Jerick Shi

Keywords: multi-agent systems, algorithmic trading, organizational design, financial markets, artificial intelligence, communication structure

TL;DR: Optimal communication design for multi-agent trading systems depends on market volatility: competitive structures outperform in turbulent technology stocks while collaborative structures dominate stable sectors.

Abstract: Multi-strategy hedge funds face a fundamental organizational choice: should analysts generating trading strategies communicate, and if so, how? We investigate this using 5-agent LLM-based trading systems across 450 experiments spanning 21 months, comparing five organizational structures from isolated baseline to collaborative and competitive conversation. We show that communication improves performance, but optimal communication design depends on market characteristics. Competitive conversation excels in volatile technology stocks, while collaborative conversation dominates stable general stocks. Finance stocks resist all communication interventions. Surprisingly, all structures—including isolated agents—converge to similar strategy alignments, challenging assumptions that transparency causes harmful diversity loss. Performance differences stem from behavioral mechanisms: competitive agents focus on stock-level allocation while collaborative agents develop technical frameworks. Conversation quality scores show zero correlation with returns. These findings demonstrate that optimal communication design must match market volatility characteristics, and sophisticated discussions don't guarantee better performance.

Submission Number: 115