Quantitative trading: quotes, backtesting, screening, and genetic algorithm strategy evolution.
{
"mcpServers": {
"io-github-neuzhou-stratevo": {
"command": "<see-readme>",
"args": []
}
}
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Quantitative trading: quotes, backtesting, screening, and genetic algorithm strategy evolution.
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Genetic algorithm breeds and walk-forward tests trading strategies from 484 factors.
484+ factors · Genetic evolution · Walk-forward validated · No API keys needed
⬆️ Real evolution run: 9 crypto assets × 600 generations. Fitness climbs from random (-0.95) to optimized (37.5) — 33% annual return, 6.06 Sharpe, 5.6% max drawdown. (backtest result, not live trading)
Quick Start · Why StratEvo? · How It Works · MCP Server · Discord
pip install stratevo
stratevo evolve --quick # See results in ~2 minutes
stratevo evolve --market crypto # Full evolution (deeper search)
No API keys. No exchange accounts. No config files. From install to first evolved strategy in under 2 minutes.
$ stratevo evolve --quick
⚡ Quick mode — small dataset, fast iterations
Results in ~2 minutes. Use without --quick for full evolution.
============================================================
StratEvo Auto Evolution Engine
============================================================
[factors] loaded 480 dynamic factors
Population: 15 | Elite: 3 | Mutation rate: 0.5
------------------------------------------------------------
Gen 0 | fitness= -1.00 | return= 0.0% | sharpe=-0.74 | trades= 0 | 28s
Gen 5 | fitness= 1.23 | return= 12.4% | sharpe= 0.85 | trades= 14 | 25s
Gen 10 | fitness= 3.60 | return= 18.7% | sharpe= 1.40 | trades= 23 | 27s
═══════════════════════════════════════════
🏆 Best Strategy Found
═══════════════════════════════════════════
Generation: 10
Fitness: 3.60
Annual Return: 18.7%
Sharpe Ratio: 1.40
Max Drawdown: 12.3%
Walk-Forward OOS Results:
Window 0: +6.4% (6 trades) ✅
Window 1: -2.1% (17 trades) ❌
Window 2: +17.2% (14 trades) ✅
Profitable: 2/3 windows
Top Factors:
crypto_bollinger_fast 0.0226 ████
momentum_3d 0.0187 ███
previous_low_test
... [View full README on GitHub](https://github.com/NeuZhou/stratevo#readme)