feat: Multi-Pair Divergence Selection Strategy

- 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

scripts/run_multi_pair_backtest.py

@@ -0,0 +1,156 @@
+#!/usr/bin/env python3
+"""
+Run Multi-Pair Divergence Strategy backtest and compare with baseline.
+
+Compares the multi-pair strategy against the single-pair BTC/ETH regime strategy.
+"""
+import sys
+sys.path.insert(0, '.')
+
+from engine.backtester import Backtester
+from engine.data_manager import DataManager
+from engine.logging_config import setup_logging, get_logger
+from engine.reporting import Reporter
+from strategies.multi_pair import MultiPairDivergenceStrategy, MultiPairConfig
+from strategies.regime_strategy import RegimeReversionStrategy
+from engine.market import MarketType
+
+logger = get_logger(__name__)
+
+
+def run_baseline():
+    """Run baseline BTC/ETH regime strategy."""
+    logger.info("=" * 60)
+    logger.info("BASELINE: BTC/ETH Regime Reversion Strategy")
+    logger.info("=" * 60)
+    
+    dm = DataManager()
+    bt = Backtester(dm)
+    
+    strategy = RegimeReversionStrategy()
+    
+    result = bt.run_strategy(
+        strategy,
+        'okx',
+        'ETH-USDT',
+        timeframe='1h',
+        init_cash=10000
+    )
+    
+    logger.info("Baseline Results:")
+    logger.info("  Total Return: %.2f%%", result.portfolio.total_return() * 100)
+    logger.info("  Total Trades: %d", result.portfolio.trades.count())
+    logger.info("  Win Rate: %.1f%%", result.portfolio.trades.win_rate() * 100)
+    
+    return result
+
+
+def run_multi_pair(assets: list[str] | None = None):
+    """Run multi-pair divergence strategy."""
+    logger.info("=" * 60)
+    logger.info("MULTI-PAIR: Divergence Selection Strategy")
+    logger.info("=" * 60)
+    
+    dm = DataManager()
+    bt = Backtester(dm)
+    
+    # Use provided assets or default
+    if assets:
+        config = MultiPairConfig(assets=assets)
+    else:
+        config = MultiPairConfig()
+    
+    logger.info("Configured %d assets, %d pairs", len(config.assets), config.get_pair_count())
+    
+    strategy = MultiPairDivergenceStrategy(config=config)
+    
+    result = bt.run_strategy(
+        strategy,
+        'okx',
+        'ETH-USDT',  # Reference asset (not used for trading, just index alignment)
+        timeframe='1h',
+        init_cash=10000
+    )
+    
+    logger.info("Multi-Pair Results:")
+    logger.info("  Total Return: %.2f%%", result.portfolio.total_return() * 100)
+    logger.info("  Total Trades: %d", result.portfolio.trades.count())
+    logger.info("  Win Rate: %.1f%%", result.portfolio.trades.win_rate() * 100)
+    
+    return result
+
+
+def compare_results(baseline, multi_pair):
+    """Compare and display results."""
+    logger.info("=" * 60)
+    logger.info("COMPARISON")
+    logger.info("=" * 60)
+    
+    baseline_return = baseline.portfolio.total_return() * 100
+    multi_return = multi_pair.portfolio.total_return() * 100
+    
+    improvement = multi_return - baseline_return
+    
+    logger.info("Baseline Return:    %.2f%%", baseline_return)
+    logger.info("Multi-Pair Return:  %.2f%%", multi_return)
+    logger.info("Improvement:        %.2f%% (%.1fx)", 
+                improvement, 
+                multi_return / baseline_return if baseline_return != 0 else 0)
+    
+    baseline_trades = baseline.portfolio.trades.count()
+    multi_trades = multi_pair.portfolio.trades.count()
+    
+    logger.info("Baseline Trades:    %d", baseline_trades)
+    logger.info("Multi-Pair Trades:  %d", multi_trades)
+    
+    return {
+        'baseline_return': baseline_return,
+        'multi_pair_return': multi_return,
+        'improvement': improvement,
+        'baseline_trades': baseline_trades,
+        'multi_pair_trades': multi_trades
+    }
+
+
+def main():
+    """Main entry point."""
+    setup_logging()
+    
+    # Check available assets
+    dm = DataManager()
+    available = []
+    
+    for symbol in MultiPairConfig().assets:
+        try:
+            dm.load_data('okx', symbol, '1h', market_type=MarketType.PERPETUAL)
+            available.append(symbol)
+        except FileNotFoundError:
+            pass
+    
+    if len(available) < 2:
+        logger.error(
+            "Need at least 2 assets to run multi-pair strategy. "
+            "Run: uv run python scripts/download_multi_pair_data.py"
+        )
+        return
+    
+    logger.info("Found data for %d assets: %s", len(available), available)
+    
+    # Run baseline
+    baseline_result = run_baseline()
+    
+    # Run multi-pair
+    multi_result = run_multi_pair(available)
+    
+    # Compare
+    comparison = compare_results(baseline_result, multi_result)
+    
+    # Save reports
+    reporter = Reporter()
+    reporter.save_reports(multi_result, "multi_pair_divergence")
+    
+    logger.info("Reports saved to backtest_logs/")
+
+
+if __name__ == "__main__":
+    main()