From 12bc699ddba1aa0371eb4dc2e1e1436611c92a5c Mon Sep 17 00:00:00 2001
From: root <root@ollama-dell.localdomain>
Date: Sat, 28 Mar 2026 20:05:21 +0400
Subject: [PATCH] Add Phase 2 trading rules documentation and data README

---
 data/README.md       | 35 +++++++++++++++++++++
 docs/PHASE2_RULES.md | 74 ++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 109 insertions(+)
 create mode 100644 data/README.md
 create mode 100644 docs/PHASE2_RULES.md

diff --git a/data/README.md b/data/README.md
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+# Data Directory
+
+CSV files are not tracked in git (too large).
+
+## Required files
+```
+EURUSD_5M.csv
+GBPUSD_5M.csv
+USDJPY_5M.csv
+```
+
+## How to obtain data
+
+1. Download 1-minute data from [HistData.com](https://www.histdata.com/):
+   - EURUSD, GBPUSD, USDJPY
+   - Years 2024, 2025, and 2026 (Jan-Mar)
+   - 1-minute bar format (MetaTrader compatible)
+
+2. Place `.zip` files in this directory
+
+3. Run the resampling script:
+   ```bash
+   python3 ../scripts/resample_to_5m.py
+   ```
+
+This produces the `*_5M.csv` files needed for training.
+
+## Data format
+
+CSV columns:
+```
+open,high,low,close,volume
+1.07451,1.07481,1.07432,1.07465,12345
+...
+```
diff --git a/docs/PHASE2_RULES.md b/docs/PHASE2_RULES.md
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+# Phase 2 Trading Rules
+
+## Signal Generation
+- Source: Genetic Programming tree evolved over 3000 individuals × 30 generations
+- Input features: EURUSD, GBPUSD, USDJPY OHLC (12 inputs total)
+- Output: Continuous signal -100 to +100
+- Long entry: signal > +5.0
+- Short entry: signal < -5.0
+- Dead band: -5.0 to +5.0 (no trade)
+
+## Per Trade Risk Management
+| Parameter | Value |
+|-----------|-------|
+| Trade size (training) | $1,000 USD |
+| Trade size (live) | $300 USD |
+| Max concurrent (live) | 3 trades |
+| Max exposure (live) | $900 USD |
+| Initial SL | 1x ATR below/above entry |
+| Trail trigger | 3x ATR profit from entry |
+| Trail distance | 15% behind current price |
+| Close condition | 15% reversal from peak/trough |
+
+## Long Trade Example
+```
+Entry: 150.00 USDJPY
+ATR: 0.30
+SL initial: 149.70 (150.00 - 1×0.30)
+Trail activates: 150.90 (150.00 + 3×0.30)
+
+Price moves to: 151.00
+New SL: 128.35 (151.00 × 0.85)
+
+Price moves to: 152.00
+New SL: 129.20 (152.00 × 0.85)
+
+Price drops to: 129.20 → CLOSE
+Profit: ~1:7 risk/reward
+```
+
+## Short Trade Example
+```
+Entry: 150.00 USDJPY
+ATR: 0.30
+SL initial: 150.30 (150.00 + 1×0.30)
+Trail activates: 149.10 (150.00 - 3×0.30)
+
+Price drops to: 149.00
+New SL: 171.35 (149.00 × 1.15)
+
+Price drops to: 148.00
+New SL: 170.20 (148.00 × 1.15)
+
+Price rises to: 170.20 → CLOSE
+Profit: ~1:7 risk/reward
+```
+
+## Fitness Function
+Win rate is PRIMARY objective (weight 6.0):
+```python
+win_bonus = (win_rate - 50.0) / 10.0
+trade_penalty = max(0.0, (n_trades - 3000) / 10000.0)
+fitness = -(6.0 * win_bonus) - (0.5 * sharpe) - (0.1 * total_ret / 10.0) + trade_penalty
+```
+- 80% win rate → win_bonus = +3.0 → strong reward
+- 50% win rate → win_bonus = 0.0 → neutral
+- 40% win rate → win_bonus = -1.0 → penalised
+
+## Backtesting Configuration
+- Library: vectorbt 0.28.5
+- Train: Jan 2024 – Jun 2025 (44,310 bars)
+- Validation: Jul 2025 – Oct 2025 (10,079 bars)
+- Test: Nov 2025 – Mar 2026 (6,420 bars)
+- Commission: 0.0015% per side
+- Initial cash: $100,000