feat: add PyP quant strategy templates

2026-08-26 09:08:07 +00:00 · 2026-04-06 10:59:38 +00:00
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+# PyP Quant Trading Strategy Templates
+
+Open-source Python quant trading strategy templates for PyP Quant Mode.
+
+This repository is a public, educational starter library for traders who want to build quantitative trading strategies with Python, validate them with PyP PPE simulation, and deploy live signals through the PyP platform.
+
+These examples are intentionally safe starter projects. They are not financial advice, not live performance claims, and not recommendations to trade any instrument.
+
+## What Is Inside
+
+Each template follows the PyP Quant Mode contract:
+
+```python
+def train(data, config):
+    return model, metrics
+
+def predict(model, market_data, config):
+    return {"signal": "UP|DOWN|HOLD", "confidence": 0.0, "metadata": {}}
+```
+
+Every project includes:
+
+- `strategy.py`
+- `quant.config.json`
+- `README.md`
+
+## Templates
+
+| Template | Pair | Timeframe | Model family | Use case |
+| --- | --- | --- | --- | --- |
+| `eurusd-logistic-15m` | EURUSD | 15m | sklearn | Baseline directional classifier |
+| `eurusd-xgboost-1h` | EURUSD | 1h | XGBoost | Feature-rich trend classifier |
+| `gbpusd-breakout-rf` | GBPUSD | 30m | sklearn RandomForest | Range breakout classifier |
+| `usdjpy-mean-reversion` | USDJPY | 1h | sklearn | Mean reversion baseline |
+| `xauusd-regime-xgboost-v11` | XAUUSD | 1h | XGBoost | Less restrictive Au-79-style gold model |
+| `xauusd-atr-breakout` | XAUUSD | 15m | custom Python | ATR breakout rules |
+| `btcusdt-lightgbm-1h` | BTCUSDT | 1h | LightGBM | Crypto trend classifier |
+| `ethusdt-volatility-classifier` | ETHUSDT | 30m | sklearn | Volatility regime classifier |
+| `solusdt-scalp-baseline` | SOLUSDT | 1m | custom Python | High-volatility scalp baseline |
+| `onnx-export-sklearn-starter` | EURUSD | 1h | sklearn to ONNX | ONNX export starter |
+| `statsmodels-arima-direction` | EURUSD | 1h | statsmodels | Statistical direction baseline |
+| `lightgbm-fx-multifeature` | EURUSD | 30m | LightGBM | Multi-feature FX classifier |
+
+## Use With PyP
+
+1. Open PyP Quant Mode:
+   https://pyp.stanlink.online/projects/quant/new
+2. Create a new quant project.
+3. Copy a template's `strategy.py` and `quant.config.json`.
+4. Run a training job.
+5. Validate with PPE simulation.
+6. Deploy only after the strategy produces acceptable out-of-sample behavior.
+
+## PyP Links
+
+- Quant landing page: https://pyp.stanl.ink/for-quant-traders
+- Quant docs: https://pyp.stanl.ink/docs/quant/what-is-quant-mode
+- Create a quant project: https://pyp.stanlink.online/projects/quant/new
+
+## Risk Disclaimer
+
+Trading foreign exchange, CFDs, crypto, and leveraged products involves substantial risk. These templates are educational examples only. Past performance and simulated results do not guarantee future performance.