Add check_symbols.py for ETH perpetuals filtering and enhance backtester with size handling

- Introduced `check_symbols.py` to load and filter ETH perpetual markets from the OKX exchange using CCXT.
- Updated the backtester to normalize signals to a 5-tuple format, incorporating size management for trades.
- Enhanced portfolio functions to support variable size and leverage adjustments based on initial capital.
- Added a new method in `CryptoQuantClient` for chunked historical data fetching to avoid API limits.
- Improved market symbol normalization in `market.py` to handle different formats.
- Updated regime strategy parameters based on recent research findings for optimal performance.

strategies/factory.py

@@ -80,14 +80,23 @@ def _build_registry() -> dict[str, StrategyConfig]:
         "regime": StrategyConfig(
             strategy_class=RegimeReversionStrategy,
             default_params={
-                'horizon': 96,
-                'z_window': 24,
-                'stop_loss': 0.06,
-                'take_profit': 0.05
+                # Optimal from walk-forward research (research/horizon_optimization_results.csv)
+                'horizon': 102,           # 4.25 days - best Net PnL
+                'z_window': 24,           # 24h rolling Z-score window
+                'z_entry_threshold': 1.0, # Enter when |Z| > 1.0
+                'profit_target': 0.005,   # 0.5% target for ML labels
+                'stop_loss': 0.06,        # 6% stop loss
+                'take_profit': 0.05,      # 5% take profit
+                'train_ratio': 0.7,       # 70% train / 30% test
+                'trend_window': 0,        # Disabled SMA filter
+                'use_funding_filter': True, # Enabled Funding filter
+                'funding_threshold': 0.005  # 0.005% threshold (Proven profitable)
             },
             grid_params={
-                'horizon': [72, 96, 120],
-                'stop_loss': [0.04, 0.06, 0.08]
+                'horizon': [84, 96, 102, 108, 120],
+                'z_entry_threshold': [0.8, 1.0, 1.2],
+                'stop_loss': [0.04, 0.06, 0.08],
+                'funding_threshold': [0.005, 0.01, 0.02]
             }
         )
     }