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Simon Moisy 1af0aab5fa feat: Add Multi-Pair Divergence Live Trading Module

- Introduced a new module for live trading based on the Multi-Pair Divergence Strategy.
- Implemented configuration classes for OKX API and multi-pair settings.
- Developed data feed functionality to fetch real-time OHLCV and funding data for multiple assets.
- Created a trading bot orchestrator to manage trading cycles, including entry and exit signals based on ML model predictions.
- Added comprehensive logging and error handling for robust operation.
- Included a README with setup instructions and usage guidelines for the new module.

2026-01-15 22:17:13 +08:00

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Multi-Pair Divergence Live Trading

This module implements live trading for the Multi-Pair Divergence Selection Strategy on OKX perpetual futures.

Overview

The strategy scans 10 cryptocurrency pairs for spread divergence opportunities:

Pair Universe: Top 10 assets by market cap (BTC, ETH, SOL, XRP, BNB, DOGE, ADA, AVAX, LINK, DOT)
Spread Z-Score: Identifies when pairs are divergent from their historical mean
Universal ML Model: Predicts probability of successful mean reversion
Dynamic Selection: Trades the pair with highest divergence score

Prerequisites

Before running live trading, you must train the model via backtesting:

uv run python scripts/run_multi_pair_backtest.py

This creates data/multi_pair_model.pkl which the live trading bot requires.

Setup

1. API Keys

Same as single-pair trading. Set in .env:

OKX_API_KEY=your_api_key
OKX_SECRET=your_secret
OKX_PASSWORD=your_passphrase
OKX_DEMO_MODE=true  # Use demo for testing

2. Dependencies

All dependencies are in pyproject.toml. No additional installation needed.

Usage

Run with Demo Account (Recommended First)

uv run python -m live_trading.multi_pair.main

Command Line Options

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

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

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

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

Live Trading (Use with Caution)

uv run python -m live_trading.multi_pair.main --live

How It Works

Each Trading Cycle

Fetch Data: Gets OHLCV for all 10 assets from OKX
Calculate Features: Computes Z-Score, RSI, volatility for all 45 pair combinations
Score Pairs: Uses ML model to rank pairs by divergence score (|Z| x probability)
Check Exits: If holding, check mean reversion or SL/TP
Enter Best: If no position, enter the highest-scoring divergent pair

Entry Conditions

|Z-Score| > 1.0 (spread diverged from mean)
ML probability > 0.5 (model predicts successful reversion)
Funding rate filter passes (avoid crowded trades)

Exit Conditions

Mean reversion: |Z-Score| returns to ~0
Stop-loss: ATR-based (default ~6%)
Take-profit: ATR-based (default ~5%)

Strategy Parameters

Parameter	Default	Description
`z_entry_threshold`	1.0	Enter when \|Z-Score\| > threshold
`z_exit_threshold`	0.0	Exit when Z reverts to mean
`z_window`	24	Rolling window for Z-Score (hours)
`prob_threshold`	0.5	ML probability threshold for entry
`funding_threshold`	0.0005	Funding rate filter (0.05%)
`sl_atr_multiplier`	10.0	Stop-loss as ATR multiple
`tp_atr_multiplier`	8.0	Take-profit as ATR multiple

Files

Input

data/multi_pair_model.pkl - Pre-trained ML model (required)

Output

logs/multi_pair_live.log - Trading logs
live_trading/multi_pair_positions.json - Position persistence
live_trading/multi_pair_trade_log.csv - Trade history

Architecture

live_trading/multi_pair/
    __init__.py          # Module exports
    config.py            # Configuration classes
    data_feed.py         # Multi-asset OHLCV fetcher
    strategy.py          # ML scoring and signal generation
    main.py              # Bot orchestrator
    README.md            # This file

Differences from Single-Pair

Aspect	Single-Pair	Multi-Pair
Assets	ETH only (BTC context)	10 assets, 45 pairs
Model	ETH-specific	Universal across pairs
Selection	Fixed pair	Dynamic best pair
Stops	Fixed 6%/5%	ATR-based dynamic

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
The model was trained on historical data and may not predict future performance

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