williams data structure in data provider
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@ -31,7 +31,7 @@ from .extrema_trainer import ExtremaTrainer
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from .trading_action import TradingAction
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from .negative_case_trainer import NegativeCaseTrainer
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from .trading_executor import TradingExecutor
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from training.enhanced_pivot_rl_trainer import EnhancedPivotRLTrainer, create_enhanced_pivot_trainer
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# Enhanced pivot RL trainer functionality integrated into orchestrator
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logger = logging.getLogger(__name__)
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@ -158,19 +158,12 @@ class EnhancedTradingOrchestrator:
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self.current_positions = {} # symbol -> {'side': 'LONG'|'SHORT'|'FLAT', 'entry_price': float, 'timestamp': datetime}
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self.last_signals = {} # symbol -> {'action': 'BUY'|'SELL', 'timestamp': datetime, 'confidence': float}
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# Initialize Enhanced Pivot RL Trainer
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self.pivot_rl_trainer = create_enhanced_pivot_trainer(
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data_provider=self.data_provider,
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orchestrator=self
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)
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# Pivot-based dynamic thresholds (simplified without external trainer)
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self.entry_threshold = 0.7 # Higher threshold for entries
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self.exit_threshold = 0.3 # Lower threshold for exits
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self.uninvested_threshold = 0.4 # Stay out threshold
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# Get dynamic thresholds from pivot trainer
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thresholds = self.pivot_rl_trainer.get_current_thresholds()
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self.entry_threshold = thresholds['entry_threshold'] # Higher threshold for entries
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self.exit_threshold = thresholds['exit_threshold'] # Lower threshold for exits
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self.uninvested_threshold = thresholds['uninvested_threshold'] # Stay out threshold
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logger.info(f"Dynamic Pivot-Based Thresholds:")
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logger.info(f"Pivot-Based Thresholds:")
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logger.info(f" Entry threshold: {self.entry_threshold:.3f} (more certain)")
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logger.info(f" Exit threshold: {self.exit_threshold:.3f} (easier to exit)")
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logger.info(f" Uninvested threshold: {self.uninvested_threshold:.3f} (stay out when uncertain)")
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