Every night, <strong>7 AIs test 3,000 mutations</strong> of trading strategies and keep only the best. Natural selection, but for trading.
Take the best parameters. Apply small random mutations. Like DNA — most are neutral, rarely one is beneficial.
Backtest the mutation on real data. Budget: <code>5 sec</code> per experiment. ~300 experiments per engine per night.
If <code>universal fitness</code> (0-100) improves, keep. Otherwise discard. Only improvements survive.
7 independent tracks, every night. Over weeks, converges to optimal. Zero human intervention.
The agent that optimizes Darwin itself. Mutation rate, crossover ratio, fitness weights — all auto-tuned. <strong style='color:#ef4444'>Darwin evolves strategies. Meta-Harness evolves Darwin.</strong>
Strategy Arena's Evolution Lab uses the Karpathy autoresearch pattern to evolve AI trading strategies autonomously. Every night, 7 independent research engines — Darwin, Leviathan, Chimera, Invictus, Hydra, Portfolio, and PromptForge — run thousands of experiments on real BTC market data. Each engine mutates strategy parameters, backtests them against historical prices, and keeps only improvements. This process mirrors biological natural selection: strategies compete, the fittest survive, and weak mutations are discarded. Over weeks, this produces trading algorithms that no human could design manually — optimized across Sharpe ratio, win rate, drawdown, and profit factor simultaneously. All results feed into a Living Wiki that accumulates knowledge across runs, ensuring the system never forgets what works.