Simon Moisy
0c82c4f366
- Added FastAPI backend with core API endpoints for strategies, backtests, and data management. - Introduced Vue 3 frontend with a dark theme, enabling users to run backtests, adjust parameters, and compare results. - Implemented Pydantic schemas for request/response validation and SQLAlchemy models for database interactions. - Enhanced project structure with dedicated modules for services, routers, and components. - Updated dependencies in `pyproject.toml` and `frontend/package.json` to include FastAPI, SQLAlchemy, and Vue-related packages. - Improved `.gitignore` to exclude unnecessary files and directories.
136 lines
3.8 KiB
Markdown
136 lines
3.8 KiB
Markdown
# Live Trading - Regime Reversion Strategy
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This module implements live trading for the ML-based regime detection and mean reversion strategy on OKX perpetual futures.
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## Overview
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The strategy trades ETH perpetual futures based on:
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1. **BTC/ETH Spread Z-Score**: Identifies when ETH is cheap or expensive relative to BTC
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2. **Random Forest ML Model**: Predicts probability of successful mean reversion
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3. **Funding Rate Filter**: Avoids trades in overheated/oversold market conditions
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## Setup
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### 1. API Keys
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The bot loads OKX API credentials from `../BTC_spot_MVRV/.env`.
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**IMPORTANT: OKX uses SEPARATE API keys for live vs demo trading!**
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#### Option A: Demo Trading (Recommended for Testing)
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1. Go to [OKX Demo Trading](https://www.okx.com/demo-trading)
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2. Create a demo account if you haven't
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3. Generate API keys from the demo environment
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4. Set in `.env`:
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```env
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OKX_API_KEY=your_demo_api_key
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OKX_SECRET=your_demo_secret
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OKX_PASSWORD=your_demo_passphrase
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OKX_DEMO_MODE=true
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```
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#### Option B: Live Trading (Real Funds)
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Use your existing live API keys with:
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```env
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OKX_API_KEY=your_live_api_key
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OKX_SECRET=your_live_secret
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OKX_PASSWORD=your_live_passphrase
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OKX_DEMO_MODE=false
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```
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**Note:** You cannot use live API keys with `OKX_DEMO_MODE=true` or vice versa.
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OKX will return error `50101: APIKey does not match current environment`.
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### 2. Dependencies
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All dependencies are already in the project's `pyproject.toml`. No additional installation needed.
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## Usage
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### Run with Demo Account (Recommended First)
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```bash
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cd /path/to/lowkey_backtest
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uv run python -m live_trading.main
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```
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### Command Line Options
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```bash
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# Custom position size
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uv run python -m live_trading.main --max-position 500
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# Custom leverage
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uv run python -m live_trading.main --leverage 2
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# Custom cycle interval (in seconds)
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uv run python -m live_trading.main --interval 1800
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# Combine options
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uv run python -m live_trading.main --max-position 1000 --leverage 3 --interval 3600
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```
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### Live Trading (Use with Caution)
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```bash
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# Requires OKX_DEMO_MODE=false in .env
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uv run python -m live_trading.main --live
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```
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## Architecture
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```
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live_trading/
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__init__.py # Module initialization
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config.py # Configuration loading
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okx_client.py # OKX API wrapper
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data_feed.py # Real-time OHLCV data
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position_manager.py # Position tracking
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live_regime_strategy.py # Strategy logic
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main.py # Entry point
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.env.example # Environment template
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README.md # This file
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```
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## Strategy Parameters
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| Parameter | Default | Description |
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|-----------|---------|-------------|
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| `z_entry_threshold` | 1.0 | Enter when \|Z-Score\| > threshold |
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| `z_window` | 24 | Rolling window for Z-Score (hours) |
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| `model_prob_threshold` | 0.5 | ML probability threshold for entry |
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| `funding_threshold` | 0.005 | Funding rate filter threshold |
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| `stop_loss_pct` | 6% | Stop-loss percentage |
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| `take_profit_pct` | 5% | Take-profit percentage |
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## Files Generated
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- `live_trading/positions.json` - Open positions persistence
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- `live_trading/trade_log.csv` - Trade history
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- `live_trading/regime_model.pkl` - Trained ML model
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- `logs/live_trading.log` - Trading logs
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## Risk Warning
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This is experimental trading software. Use at your own risk:
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- Always start with demo trading
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- Never risk more than you can afford to lose
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- Monitor the bot regularly
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- Have a kill switch ready (Ctrl+C)
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## Troubleshooting
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### API Key Issues
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- Ensure API keys have trading permissions
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- For demo trading, use demo-specific API keys
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- Check that passphrase matches exactly
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### No Signals Generated
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- The strategy requires the ML model to be trained
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- Need at least 200 candles of data
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- Model trains automatically on first run
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### Position Sync Issues
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- The bot syncs with exchange positions on each cycle
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- If positions are closed manually, the bot will detect this
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