eca17b42fe
Phase 1 completion: - Add DataStreamer for real-time Binance Futures WebSocket data (klines, mark price) - Add DataValidator for candle validation and gap detection - Add timeframes module with interval mappings Phase 2 foundation: - Add RegimeClassifier with ADX/ATR/Bollinger Band analysis - Add Regime enum (TRENDING_UP/DOWN, RANGING, HIGH_VOLATILITY, UNCERTAIN) - Add Strategy ABC defining generate_signal, get_stop_loss, parameters, suitable_regimes - Add Signal dataclass and SignalType enum for strategy outputs Testing: - Add comprehensive test suites for all new modules - 159 tests passing, 24 skipped (async WebSocket timing) - 82% code coverage Dependencies: - Add pandas-stubs to dev dependencies for mypy compatibility
88 lines
2.7 KiB
Python
88 lines
2.7 KiB
Python
"""Signal types for trading strategies."""
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from dataclasses import dataclass, field
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from datetime import datetime
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from decimal import Decimal
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from enum import Enum
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from typing import Any
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import structlog
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logger = structlog.get_logger(__name__)
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class SignalType(str, Enum):
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"""Type of trading signal."""
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ENTRY_LONG = "entry_long"
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ENTRY_SHORT = "entry_short"
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EXIT_LONG = "exit_long"
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EXIT_SHORT = "exit_short"
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@dataclass
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class Signal:
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"""Trading signal emitted by a strategy.
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Attributes:
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signal_type: Type of signal (entry/exit, long/short)
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symbol: Trading symbol (e.g., "BTCUSDT")
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price: Suggested entry/exit price
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stop_loss: Stop loss price for risk calculation
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take_profit: Optional take profit price
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confidence: Signal confidence from 0.0 to 1.0
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timestamp: When the signal was generated
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strategy_name: Name of the strategy that generated the signal
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metadata: Additional signal-specific data
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"""
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signal_type: SignalType
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symbol: str
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price: Decimal
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stop_loss: Decimal
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take_profit: Decimal | None
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confidence: float
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timestamp: datetime
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strategy_name: str
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metadata: dict[str, Any] = field(default_factory=dict)
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def __post_init__(self) -> None:
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"""Validate signal parameters."""
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if not 0.0 <= self.confidence <= 1.0:
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raise ValueError(f"Confidence must be between 0.0 and 1.0, got {self.confidence}")
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if self.price <= Decimal("0"):
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raise ValueError(f"Price must be positive, got {self.price}")
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if self.stop_loss <= Decimal("0"):
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raise ValueError(f"Stop loss must be positive, got {self.stop_loss}")
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@property
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def is_entry(self) -> bool:
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"""Check if this is an entry signal."""
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return self.signal_type in (SignalType.ENTRY_LONG, SignalType.ENTRY_SHORT)
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@property
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def is_exit(self) -> bool:
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"""Check if this is an exit signal."""
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return self.signal_type in (SignalType.EXIT_LONG, SignalType.EXIT_SHORT)
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@property
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def is_long(self) -> bool:
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"""Check if this is a long-side signal."""
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return self.signal_type in (SignalType.ENTRY_LONG, SignalType.EXIT_LONG)
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@property
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def is_short(self) -> bool:
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"""Check if this is a short-side signal."""
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return self.signal_type in (SignalType.ENTRY_SHORT, SignalType.EXIT_SHORT)
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@property
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def risk_reward_ratio(self) -> Decimal | None:
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"""Calculate risk/reward ratio if take profit is set."""
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if self.take_profit is None:
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return None
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risk = abs(self.price - self.stop_loss)
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reward = abs(self.take_profit - self.price)
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if risk == Decimal("0"):
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return None
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return reward / risk
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