Simon Moisy
df37366603
- Extend regime detection to top 10 cryptocurrencies (45 pairs) - Dynamic pair selection based on divergence score (|z_score| * probability) - Universal ML model trained on all pairs - Correlation-based filtering to avoid redundant positions - Funding rate integration from OKX for all 10 assets - ATR-based dynamic stop-loss and take-profit - Walk-forward training with 70/30 split Performance: +35.69% return (vs +28.66% baseline), 63.6% win rate
157 lines
4.5 KiB
Python
157 lines
4.5 KiB
Python
#!/usr/bin/env python3
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"""
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Run Multi-Pair Divergence Strategy backtest and compare with baseline.
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Compares the multi-pair strategy against the single-pair BTC/ETH regime strategy.
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"""
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import sys
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sys.path.insert(0, '.')
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from engine.backtester import Backtester
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from engine.data_manager import DataManager
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from engine.logging_config import setup_logging, get_logger
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from engine.reporting import Reporter
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from strategies.multi_pair import MultiPairDivergenceStrategy, MultiPairConfig
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from strategies.regime_strategy import RegimeReversionStrategy
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from engine.market import MarketType
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logger = get_logger(__name__)
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def run_baseline():
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"""Run baseline BTC/ETH regime strategy."""
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logger.info("=" * 60)
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logger.info("BASELINE: BTC/ETH Regime Reversion Strategy")
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logger.info("=" * 60)
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dm = DataManager()
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bt = Backtester(dm)
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strategy = RegimeReversionStrategy()
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result = bt.run_strategy(
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strategy,
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'okx',
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'ETH-USDT',
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timeframe='1h',
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init_cash=10000
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)
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logger.info("Baseline Results:")
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logger.info(" Total Return: %.2f%%", result.portfolio.total_return() * 100)
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logger.info(" Total Trades: %d", result.portfolio.trades.count())
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logger.info(" Win Rate: %.1f%%", result.portfolio.trades.win_rate() * 100)
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return result
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def run_multi_pair(assets: list[str] | None = None):
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"""Run multi-pair divergence strategy."""
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logger.info("=" * 60)
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logger.info("MULTI-PAIR: Divergence Selection Strategy")
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logger.info("=" * 60)
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dm = DataManager()
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bt = Backtester(dm)
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# Use provided assets or default
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if assets:
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config = MultiPairConfig(assets=assets)
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else:
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config = MultiPairConfig()
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logger.info("Configured %d assets, %d pairs", len(config.assets), config.get_pair_count())
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strategy = MultiPairDivergenceStrategy(config=config)
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result = bt.run_strategy(
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strategy,
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'okx',
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'ETH-USDT', # Reference asset (not used for trading, just index alignment)
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timeframe='1h',
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init_cash=10000
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)
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logger.info("Multi-Pair Results:")
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logger.info(" Total Return: %.2f%%", result.portfolio.total_return() * 100)
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logger.info(" Total Trades: %d", result.portfolio.trades.count())
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logger.info(" Win Rate: %.1f%%", result.portfolio.trades.win_rate() * 100)
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return result
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def compare_results(baseline, multi_pair):
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"""Compare and display results."""
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logger.info("=" * 60)
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logger.info("COMPARISON")
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logger.info("=" * 60)
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baseline_return = baseline.portfolio.total_return() * 100
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multi_return = multi_pair.portfolio.total_return() * 100
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improvement = multi_return - baseline_return
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logger.info("Baseline Return: %.2f%%", baseline_return)
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logger.info("Multi-Pair Return: %.2f%%", multi_return)
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logger.info("Improvement: %.2f%% (%.1fx)",
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improvement,
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multi_return / baseline_return if baseline_return != 0 else 0)
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baseline_trades = baseline.portfolio.trades.count()
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multi_trades = multi_pair.portfolio.trades.count()
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logger.info("Baseline Trades: %d", baseline_trades)
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logger.info("Multi-Pair Trades: %d", multi_trades)
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return {
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'baseline_return': baseline_return,
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'multi_pair_return': multi_return,
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'improvement': improvement,
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'baseline_trades': baseline_trades,
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'multi_pair_trades': multi_trades
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}
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def main():
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"""Main entry point."""
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setup_logging()
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# Check available assets
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dm = DataManager()
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available = []
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for symbol in MultiPairConfig().assets:
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try:
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dm.load_data('okx', symbol, '1h', market_type=MarketType.PERPETUAL)
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available.append(symbol)
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except FileNotFoundError:
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pass
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if len(available) < 2:
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logger.error(
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"Need at least 2 assets to run multi-pair strategy. "
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"Run: uv run python scripts/download_multi_pair_data.py"
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)
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return
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logger.info("Found data for %d assets: %s", len(available), available)
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# Run baseline
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baseline_result = run_baseline()
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# Run multi-pair
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multi_result = run_multi_pair(available)
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# Compare
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comparison = compare_results(baseline_result, multi_result)
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# Save reports
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reporter = Reporter()
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reporter.save_reports(multi_result, "multi_pair_divergence")
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logger.info("Reports saved to backtest_logs/")
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if __name__ == "__main__":
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main()
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