7ccd8c4b04
Remove backtest.py, backtest_gpu.py, metrics.py, local CSV data, Dukascopy loader, and all backtest CLI modes from main.py. Rebalance engine weights: leading indicators (divergence, RSI, stochastic, BB) now carry 66% of signal weight vs 34% for lagging (EMA, MACD). Add ws_twelvedata.py for live tick streaming. Drop pyarrow and tqdm deps.
159 lines
3.7 KiB
Python
159 lines
3.7 KiB
Python
"""
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ForexBot2 — Configuration (USD/JPY focus)
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==========================================
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"""
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from dataclasses import dataclass, field
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from enum import Enum
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from typing import Dict, List
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class Timeframe(Enum):
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M1 = "1min"
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M5 = "5min"
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M15 = "15min"
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M30 = "30min"
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H1 = "1h"
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H4 = "4h"
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D1 = "1d"
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W1 = "1wk"
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class SignalStrength(Enum):
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STRONG_BUY = 2
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BUY = 1
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NEUTRAL = 0
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SELL = -1
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STRONG_SELL = -2
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class MarketSession(Enum):
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SYDNEY = "sydney"
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TOKYO = "tokyo"
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LONDON = "london"
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NEW_YORK = "new_york"
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OVERLAP_LONDON_NY = "london_ny_overlap"
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# ── Single Focus: USD/JPY ─────────────────────────────────────────
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USDJPY = "USDJPY=X"
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DISPLAY = "USD/JPY"
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PIP_VALUE = 0.01 # JPY pairs use 0.01 per pip
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@dataclass
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class TechnicalConfig:
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"""Technical indicator parameters."""
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ema_fast: int = 9
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ema_medium: int = 21
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ema_slow: int = 50
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ema_trend: int = 200
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rsi_period: int = 14
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rsi_overbought: float = 70.0
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rsi_oversold: float = 30.0
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rsi_neutral_upper: float = 60.0
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rsi_neutral_lower: float = 40.0
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macd_fast: int = 12
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macd_slow: int = 26
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macd_signal: int = 9
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bb_period: int = 20
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bb_std: float = 2.0
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atr_period: int = 14
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stoch_k: int = 14
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stoch_d: int = 3
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stoch_overbought: float = 80.0
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stoch_oversold: float = 20.0
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adx_period: int = 14
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adx_strong_trend: float = 25.0
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adx_very_strong: float = 50.0
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ichimoku_tenkan: int = 9
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ichimoku_kijun: int = 26
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ichimoku_senkou_b: int = 52
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volume_ma_period: int = 20
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pivot_lookback: int = 1
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divergence_lookback: int = 14
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disabled_indicators: List[str] = field(default_factory=list)
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@dataclass
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class SignalConfig:
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"""Signal scoring & filtering."""
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min_confidence: float = 55.0
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weights: Dict[str, float] = field(default_factory=lambda: {
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"trend": 0.25,
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"momentum": 0.20,
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"volatility": 0.15,
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"price_action": 0.15,
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"multi_timeframe": 0.15,
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"sentiment": 0.10,
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})
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mtf_agreement_threshold: int = 2 # of 3 timeframes
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cooldown_bars: int = 5
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default_risk_pct: float = 1.0
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default_rr_ratio: float = 2.0
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atr_sl_multiplier: float = 1.5 # SL distance = 1.5 × ATR
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@dataclass
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class NewsConfig:
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"""Economic calendar & sentiment."""
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tracked_currencies: List[str] = field(default_factory=lambda: ["USD", "JPY"])
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min_impact: str = "medium"
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pre_event_buffer_minutes: int = 30
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post_event_buffer_minutes: int = 15
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rss_feeds: List[str] = field(default_factory=lambda: [
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"https://www.forexlive.com/feed/",
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"https://www.fxstreet.com/rss",
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])
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@dataclass
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class FilterConfig:
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"""Regime and session filters for live signals."""
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regime_filter: bool = False
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regime_filter_timeframe: Timeframe = Timeframe.H4
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regime_filter_min_adx: float = 25.0
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session_filter: bool = False
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session_start_hour: int = 7
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session_end_hour: int = 16
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@dataclass
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class PlatformConfig:
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"""Top-level configuration."""
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technical: TechnicalConfig = field(default_factory=TechnicalConfig)
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signals: SignalConfig = field(default_factory=SignalConfig)
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news: NewsConfig = field(default_factory=NewsConfig)
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backtest: FilterConfig = field(default_factory=FilterConfig)
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symbol: str = USDJPY
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display_name: str = DISPLAY
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pip_value: float = PIP_VALUE
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primary_timeframe: Timeframe = Timeframe.H1
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confirmation_timeframes: List[Timeframe] = field(
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default_factory=lambda: [Timeframe.M15, Timeframe.H4]
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)
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data_lookback_days: int = 60
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twelve_data_api_key: str = "f563b22ffdfd4924955decbe1a8c8701"
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refresh_interval: int = 300
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log_level: str = "INFO"
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