lowkey_backtest/live_trading

Live Trading - Regime Reversion Strategy

This module implements live trading for the ML-based regime detection and mean reversion strategy on OKX perpetual futures.

Overview

The strategy trades ETH perpetual futures based on:

1. BTC/ETH Spread Z-Score: Identifies when ETH is cheap or expensive relative to BTC
2. Random Forest ML Model: Predicts probability of successful mean reversion
3. Funding Rate Filter: Avoids trades in overheated/oversold market conditions

Setup

1. API Keys

The bot loads OKX API credentials from ../BTC_spot_MVRV/.env.

IMPORTANT: OKX uses SEPARATE API keys for live vs demo trading!

Option A: Demo Trading (Recommended for Testing)

1. Go to OKX Demo Trading
2. Create a demo account if you haven't
3. Generate API keys from the demo environment
4. Set in .env:

OKX_API_KEY=your_demo_api_key
OKX_SECRET=your_demo_secret
OKX_PASSWORD=your_demo_passphrase
OKX_DEMO_MODE=true

Option B: Live Trading (Real Funds)

Use your existing live API keys with:

OKX_API_KEY=your_live_api_key
OKX_SECRET=your_live_secret
OKX_PASSWORD=your_live_passphrase
OKX_DEMO_MODE=false

Note: You cannot use live API keys with OKX_DEMO_MODE=true or vice versa. OKX will return error 50101: APIKey does not match current environment.

2. Dependencies

All dependencies are already in the project's pyproject.toml. No additional installation needed.

Usage

Run with Demo Account (Recommended First)

cd /path/to/lowkey_backtest
uv run python -m live_trading.main

Command Line Options

# Custom position size
uv run python -m live_trading.main --max-position 500

# Custom leverage
uv run python -m live_trading.main --leverage 2

# Custom cycle interval (in seconds)
uv run python -m live_trading.main --interval 1800

# Combine options
uv run python -m live_trading.main --max-position 1000 --leverage 3 --interval 3600

Live Trading (Use with Caution)

# Requires OKX_DEMO_MODE=false in .env
uv run python -m live_trading.main --live

Architecture

live_trading/
    __init__.py          # Module initialization
    config.py            # Configuration loading
    okx_client.py        # OKX API wrapper
    data_feed.py         # Real-time OHLCV data
    position_manager.py  # Position tracking
    live_regime_strategy.py  # Strategy logic
    main.py              # Entry point
    .env.example         # Environment template
    README.md            # This file

Strategy Parameters

Parameter	Default	Description
z_entry_threshold	1.0	Enter when |Z-Score| > threshold
z_window	24	Rolling window for Z-Score (hours)
model_prob_threshold	0.5	ML probability threshold for entry
funding_threshold	0.005	Funding rate filter threshold
stop_loss_pct	6%	Stop-loss percentage
take_profit_pct	5%	Take-profit percentage

Files Generated

• live_trading/positions.json - Open positions persistence
• live_trading/trade_log.csv - Trade history
• live_trading/regime_model.pkl - Trained ML model
• logs/live_trading.log - Trading logs

Risk Warning

This is experimental trading software. Use at your own risk:

• Always start with demo trading
• Never risk more than you can afford to lose
• Monitor the bot regularly
• Have a kill switch ready (Ctrl+C)

Troubleshooting

API Key Issues

• Ensure API keys have trading permissions
• For demo trading, use demo-specific API keys
• Check that passphrase matches exactly

No Signals Generated

• The strategy requires the ML model to be trained
• Need at least 200 candles of data
• Model trains automatically on first run

Position Sync Issues

• The bot syncs with exchange positions on each cycle
• If positions are closed manually, the bot will detect this