StratEvo MCP Server

<div align="center"> <br>

🦀 StratEvo

Stop writing trading strategies. Evolve them.

A genetic algorithm engine that breeds and walk-forward validates trading strategies across 484+ market factors.

<p align="center"> <img src="https://img.shields.io/badge/evolvable_factors-484+-orange" alt="484+ Evolvable Factors"> <img src="https://img.shields.io/badge/markets-US_Stocks_%7C_Crypto-blue" alt="Markets"> <img src="https://img.shields.io/badge/validation-Walk--Forward_%7C_Monte_Carlo-green" alt="Validation"> <a href="https://discord.gg/kAQD7Cj8"><img src="https://img.shields.io/discord/1488800950696284272?color=7289da&label=Discord&logo=discord&logoColor=white" alt="Discord"></a> </p> <p> <a href="#-live-signals">Live Signals</a> · <a href="#-paper-trading-performance">Paper Trading</a> · <a href="#how-it-works">How It Works</a> · <a href="#evolution-results">Results</a> · <a href="#anti-overfitting">Robustness</a> · <a href="#get-access">Get Access</a> </p> </div>

---

📡 Live Signals

Real-time buy/sell signals from evolved strategies. Updated daily. All signals are committed to git history — you can verify every one.

Latest Signals

<!-- SIGNALS_START -->

Date	Market	Action	Asset	Entry Price	DNA	Status
Signals will be posted here as Paper Trading goes live

<!-- SIGNALS_END -->

📁 Full signal history: signals/

---

📊 Paper Trading Performance

Forward-testing evolved strategies on real market data with simulated execution. No hindsight, no cherry-picking.

Paper Trading active — Crypto V13 live since 2026-04-18.

Current Paper Portfolio

<!-- PAPER_START -->

Strategy	Market	Start Date	Days	Return	Sharpe	MaxDD	Trades	Status
Crypto V13	Crypto	2026-04-18	0	—	—	—	—	🟢 Live

<!-- PAPER_END -->

📁 Daily P&L reports: paper-trading/
📈 Equity curves: paper-trading/charts/

Equity Curve (demo — real data accumulating)

Drawdown

---

How It Works

Most quant tools make you write the strategy. StratEvo evolves them instead.

You write the rules        →  StratEvo discovers the rules
You tune parameters        →  GA tunes parameters  
You test on one period     →  Walk-forward tests on multiple windows
You hope it generalizes    →  Monte Carlo measures if it does

  Random DNA population (484 factor weights + risk parameters)
       │
       ▼
  ┌──────────────────────┐
  │  Walk-Forward Test   │  Multi-window out-of-sample validation
  │  each DNA candidate  │  Real fees, slippage, position caps
  └──────────┬───────────┘
             │
             ▼
  Keep the survivors (fitness = Sharpe × Return / MaxDD)
             │
             ▼
  Mutate + Crossover → next generation
             │
             ▼
  Repeat for N generations

Each DNA is a weight vector across 484+ factors plus risk/position parameters — all evolvable:

Parameter	Range	What it controls
Factor weights (×484)	0.0–1.0	Which factors matter and how much
hold_days	2–60	Day trades through swing trades
trailing_stop	%	Trail below peak to lock in profits
market_regime	sensitivity	Reduce exposure automatically in bear markets
kelly_fraction	0–1	Position sizing from recent win rate

---

Evolution Results

Numbers from our running evolution engines. Updated as generations progress.

🇺🇸 US Stocks V8 (100 S&P 500 stocks — Gen 136)

Metric	Best DNA
Annual Return	33.5%
Sharpe Ratio	1.47
Max Drawdown	17.0%
Win Rate	55.5%
Profit Factor	1.75
Total Trades	179

₿ Crypto V13 (17 assets — Gen 53)

Metric	Best DNA
Annual Return	69.0%
Sharpe Ratio	2.27
Max Drawdown	13.0%
Win Rate	50.0%
Profit Factor	1.58
Total Trades	174

These are backtests with walk-forward validation, not live trades. That's the whole point of paper trading — proving it works forward, not just backward.

---

Anti-Overfitting

We learned this the hard way. An early version showed 25,000% returns. Turned out to be a bug — look-ahead bias.

Defense	What it does
Walk-Forward	Multi-window OOS validation. Must profit on data it never trained on.
Monte Carlo	1,000 shuffled iterations. p-value < 0.05 or it's luck.
CPCV	Combinatorial Purged Cross-Validation. Industry standard for a reason.
Arena Mode	Multiple strategies compete head-to-head. Crowded signals get penalized.
Bias Detection	Look-ahead, snooping, survivorship — flagged automatically.
Turnover Penalty	Excessive trading is punished. Real transaction costs baked in.

An honest 33% beats a fake 25,000%.

---

484+ Factors

Category	Count	Examples
Crypto-Native	200	Funding rate, whale detection, liquidation cascade
Momentum	14	ROC, acceleration, trend strength
Volume & Flow	13	OBV, smart money, Wyckoff VSA
Volatility	13	ATR, Bollinger squeeze, vol-of-vol
Mean Reversion	12	Z-score, Keltner channel position
Trend Following	14	ADX, EMA golden cross, MA fan
Qlib Alpha158	11	Microsoft Qlib compatible factors
+ 5 more categories	37	Risk, quality, price structure, sentiment, DRL

All factor weights are discovered by evolution. Zero manual tuning.

---

Strategy Styles

The algorithm converges on recognizable trading styles on its own:

Style	What the DNA learned
Value Seeker	Buys cheap, holds patient
Momentum Rider	Chases runners, dumps laggards
Mean Reverter	Bets on bounce-backs
Flow Reader	Follows the money — volume leads price
Volatility Hunter	Profits from vol expansion
Crypto Native	200 factors built for 24/7 markets

---

Get Access

StratEvo Pro includes the evolution engine, paper trading, signal generation, and live exchange connectors.

📧 Contact: neuzhou@outlook.com
💬 Discord: discord.gg/kAQD7Cj8

---

Technical Papers

• GT-Score: A Generalizable Fitness Function for Walk-Forward Strategy Evolution

---

<div align="center">

Check back daily for updated signals and paper trading results.

</div>