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TPTBusiness
bd025e50dc
Implement automatic trading protection system to prevent excessive losses: PROTECTIONS (100% original code, NOT copied from Freqtrade): - Max Drawdown Protection: Blocks trading when DD > 15% (configurable) - Cooldown Period: 4h mandatory rest after 5% loss - Stoploss Guard: Detects stoploss clusters (>5 per day) - Low Performance Filter: Filters factors with Sharpe < 0.5, Win Rate < 40% ARCHITECTURE: - Base protection interface with common utilities - 4 specialized protection implementations - ProtectionManager orchestrates all active protections - Time-based blocking with automatic expiry TESTS (32 total, ALL PASS): - 25 unit tests in test/backtesting/test_protections.py - 7 integration tests in test/integration/test_all_features.py - Tests cover: normal operation, edge cases, error handling DOCUMENTATION: - Update QWEN.md with development guidelines for AI assistant * Mandatory rules: Update QWEN.md, README, requirements.txt, tests * Pre-commit checklist * Example workflow - Update README.md with protection system features - Update project structure with new modules All code is 100% original - NO license issues with Freqtrade GPLv3.
87 lines
2.9 KiB
Python
87 lines
2.9 KiB
Python
"""
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Cooldown Period Protection
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Enforces mandatory rest periods after losses.
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"""
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from dataclasses import dataclass
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from datetime import datetime, timedelta
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from typing import Optional
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from .base import BaseProtection, ProtectionConfig, ProtectionResult, ProtectionType, ProtectionScope
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@dataclass
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class CooldownConfig(ProtectionConfig):
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"""Configuration for Cooldown protection."""
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cooldown_after_loss_pct: float = 0.05 # Cooldown after 5% loss
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cooldown_duration_hours: int = 4 # How long to wait
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class CooldownProtection(BaseProtection):
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"""
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Enforces cooling-off period after significant losses.
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Prevents revenge trading and emotional decisions by forcing
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a mandatory break after losses exceed threshold.
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"""
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def __init__(self, config: CooldownConfig):
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super().__init__(config)
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self.config: CooldownConfig = config
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self.last_loss_time: Optional[datetime] = None
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self.last_loss_pct: float = 0.0
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@property
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def scope(self) -> ProtectionScope:
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return ProtectionScope.FACTOR
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def check(
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self,
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returns: list[float],
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timestamps: list[datetime],
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current_equity: float,
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peak_equity: float,
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**kwargs
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) -> ProtectionResult:
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"""Check if cooldown should be triggered."""
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self.record_check()
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if not self.config.enabled:
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return ProtectionResult(
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should_block=False,
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reason="Protection disabled",
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protection_type=ProtectionType.COOLDOWN
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)
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# Check most recent return
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if returns:
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latest_return = returns[-1]
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latest_time = timestamps[-1] if timestamps else datetime.now()
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if latest_return < -self.config.cooldown_after_loss_pct:
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self.last_loss_time = latest_time
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self.last_loss_pct = latest_return
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# If recently had big loss, enforce cooldown
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if self.last_loss_time:
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time_since_loss = datetime.now() - self.last_loss_time
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if time_since_loss < timedelta(hours=self.config.cooldown_duration_hours):
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remaining = timedelta(hours=self.config.cooldown_duration_hours) - time_since_loss
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result = ProtectionResult(
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should_block=True,
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reason=f"Loss of {abs(self.last_loss_pct)*100:.1f}% - cooling down for {remaining.seconds // 3600}h",
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until=self.last_loss_time + timedelta(hours=self.config.cooldown_duration_hours),
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protection_type=ProtectionType.COOLDOWN,
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severity=abs(self.last_loss_pct) / self.config.cooldown_after_loss_pct
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)
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self.record_check(blocked=True)
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return result
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return ProtectionResult(
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should_block=False,
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reason="No recent significant losses",
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protection_type=ProtectionType.COOLDOWN,
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severity=0.0
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)
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