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trading works!

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This commit is contained in:
Dobromir Popov
2025-07-15 01:10:37 +03:00
parent 24230f7f79
commit 439611cf88
5 changed files with 309 additions and 16 deletions
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28
core/orchestrator.py
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@ -106,8 +106,8 @@ class TradingOrchestrator:
# Configuration - AGGRESSIVE for more training data
self.confidence_threshold = self.config.orchestrator.get('confidence_threshold', 0.15) # Lowered from 0.20
self.confidence_threshold_close = self.config.orchestrator.get('confidence_threshold_close', 0.08) # Lowered from 0.10
# we do not cap the decision frequency in time - only in confidence
# self.decision_frequency = self.config.orchestrator.get('decision_frequency', 30)
# Decision frequency limit to prevent excessive trading
self.decision_frequency = self.config.orchestrator.get('decision_frequency', 30)
self.symbols = self.config.get('symbols', ['ETH/USDT', 'BTC/USDT']) # Enhanced to support multiple symbols
# NEW: Aggressiveness parameters
@ -612,7 +612,7 @@ class TradingOrchestrator:
await self.make_trading_decision(symbol)
await asyncio.sleep(1) # Small delay between symbols
# await asyncio.sleep(self.decision_frequency)
await asyncio.sleep(self.decision_frequency)
except Exception as e:
logger.error(f"Error in trading decision loop: {e}")
await asyncio.sleep(5) # Wait before retrying
@ -930,8 +930,8 @@ class TradingOrchestrator:
# Check if enough time has passed since last decision
if symbol in self.last_decision_time:
time_since_last = (current_time - self.last_decision_time[symbol]).total_seconds()
# if time_since_last < self.decision_frequency:
# return None
if time_since_last < self.decision_frequency:
return None
# Get current market data
current_price = self.data_provider.get_current_price(symbol)
@ -1353,6 +1353,24 @@ class TradingOrchestrator:
best_action = 'HOLD'
reasoning['threshold_applied'] = True
# Signal accumulation check - require multiple confident signals
if best_action in ['BUY', 'SELL']:
required_signals = 3 # Require 3 confident signals
recent_decisions = self.get_recent_decisions(symbol, limit=5)
# Count recent signals in the same direction
same_direction_count = sum(1 for d in recent_decisions
if d.action == best_action and d.confidence > entry_threshold)
if same_direction_count < required_signals:
best_action = 'HOLD'
reasoning['signal_accumulation'] = True
reasoning['required_signals'] = required_signals
reasoning['current_signals'] = same_direction_count
logger.info(f"Signal accumulation: {same_direction_count}/{required_signals} signals for {best_action}")
else:
logger.info(f"Signal accumulation satisfied: {same_direction_count}/{required_signals} signals for {best_action}")
# Add P&L-based decision adjustment
best_action, best_confidence = self._apply_pnl_feedback(
best_action, best_confidence, current_position_pnl, symbol, reasoning