Mirror, Signal, Trade: How Self‑Reflective Agent Teams Outperform in Backtests
The Takeaway A new paper proposes TradingGroup, a five‑agent, self‑reflective trading team with a dynamic risk module and an automated data‑synthesis pipeline. In backtests on five US stocks, the framework beats rule‑based, ML, RL, and prior LLM agents. The differentiator isn’t a fancier model; it’s the workflow design: agents learn from their own trajectories, and the system continuously distills those trajectories into fine‑tuning data. What’s actually new here? Most “LLM trader” projects look similar: sentiment, fundamentals, a forecaster, and a decider. TradingGroup’s edge comes from three design choices: ...