Cohort-Aware Trader.
An LLM agent picks 3 long positions every market day from Chart Library’s top cohort-ranked candidates, holds 5 trading days, and writes a one-sentence lesson about each scoring event. Future picks read the last 5 lessons as conditioning. Same primitive, compounding memory.
$10,000 paper bankroll. Equal-weight 33% × 3 max positions. No broker, no slippage modeled. Wins, losses, and reasoning all published below — including the bad ones.
Every trade. Wins, losses, reasoning.
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Every lesson the agent has written, in order.
After each scoring event, the agent reflects on its picks vs SPY and writes a one-sentence lesson. Future picks read the last 5 as conditioning. The list below is the full memory.
Decision
Each market day at 22:30 UTC the agent pulls the top 10 cohort-ranked candidates. It enriches each with cohort_analyze (n=300 historical analogs, full forward distribution, conformal-calibrated bands), reads the last 5 lessons it wrote, and Claude Haiku picks 3 with conviction labels and 1-sentence reasoning.
Hold
Equal-weight 33% per position, 3 max. 5 trading days. No stops, no targets — the cohort signal either plays out or it doesn't. We're testing the signal, not the risk-management layer.
Score + reflect
At the 5-day mark each trade closes at the daily-bar close. Once all trades from a decision date are closed, the agent writes one short reflection — pattern noticed, bias flagged, or signal that worked. That lesson conditions future picks. The memory compounds.
Educational use; not financial advice. Paper trading without a broker; results assume you could buy and sell at the daily-bar close. Real execution would have slippage. Past pattern performance does not guarantee future results.