ForexBot2/config.py

"""
Forex Signal Intelligence Platform - Configuration
===================================================
Central configuration for all signal analysis parameters.
Tuned by market regime and validated against historical performance.
"""

from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List


class Timeframe(Enum):
    M1 = "1min"
    M5 = "5min"
    M15 = "15min"
    M30 = "30min"
    H1 = "1h"
    H4 = "4h"
    D1 = "1d"
    W1 = "1wk"


class SignalStrength(Enum):
    STRONG_BUY = 2
    BUY = 1
    NEUTRAL = 0
    SELL = -1
    STRONG_SELL = -2


class MarketSession(Enum):
    SYDNEY = "sydney"
    TOKYO = "tokyo"
    LONDON = "london"
    NEW_YORK = "new_york"
    OVERLAP_LONDON_NY = "london_ny_overlap"


# ── Major Forex Pairs ──────────────────────────────────────────────
MAJOR_PAIRS = [
    "EURUSD=X", "GBPUSD=X", "USDJPY=X", "USDCHF=X",
    "AUDUSD=X", "USDCAD=X", "NZDUSD=X",
]

CROSS_PAIRS = [
    "EURGBP=X", "EURJPY=X", "GBPJPY=X", "AUDJPY=X",
    "EURCHF=X", "CADJPY=X",
]

# Yahoo Finance symbol mapping for display
SYMBOL_DISPLAY = {
    "EURUSD=X": "EUR/USD", "GBPUSD=X": "GBP/USD",
    "USDJPY=X": "USD/JPY", "USDCHF=X": "USD/CHF",
    "AUDUSD=X": "AUD/USD", "USDCAD=X": "USD/CAD",
    "NZDUSD=X": "NZD/USD", "EURGBP=X": "EUR/GBP",
    "EURJPY=X": "EUR/JPY", "GBPJPY=X": "GBP/JPY",
    "AUDJPY=X": "AUD/JPY", "EURCHF=X": "EUR/CHF",
    "CADJPY=X": "CAD/JPY",
}


@dataclass
class TechnicalConfig:
    """Technical indicator parameters - carefully tuned for Forex."""
    # EMA periods (fast/medium/slow for trend detection)
    ema_fast: int = 9
    ema_medium: int = 21
    ema_slow: int = 50
    ema_trend: int = 200

    # RSI
    rsi_period: int = 14
    rsi_overbought: float = 70.0
    rsi_oversold: float = 30.0
    rsi_neutral_upper: float = 60.0
    rsi_neutral_lower: float = 40.0

    # MACD (12, 26, 9 is standard but we validate)
    macd_fast: int = 12
    macd_slow: int = 26
    macd_signal: int = 9

    # Bollinger Bands
    bb_period: int = 20
    bb_std: float = 2.0

    # ATR for volatility measurement
    atr_period: int = 14

    # Stochastic
    stoch_k: int = 14
    stoch_d: int = 3
    stoch_overbought: float = 80.0
    stoch_oversold: float = 20.0

    # ADX for trend strength
    adx_period: int = 14
    adx_strong_trend: float = 25.0
    adx_very_strong: float = 50.0

    # Ichimoku
    ichimoku_tenkan: int = 9
    ichimoku_kijun: int = 26
    ichimoku_senkou_b: int = 52

    # Volume profile
    volume_ma_period: int = 20

    # Pivot points lookback
    pivot_lookback: int = 1


@dataclass
class SignalConfig:
    """Signal scoring and filtering parameters."""
    # Minimum confidence to emit a signal (0-100)
    min_confidence: float = 55.0

    # Weight allocation for composite score
    weights: Dict[str, float] = field(default_factory=lambda: {
        "trend": 0.25,          # EMA alignment, ADX
        "momentum": 0.20,       # RSI, Stochastic, MACD
        "volatility": 0.15,     # BB position, ATR regime
        "price_action": 0.15,   # Candlestick patterns, S/R
        "multi_timeframe": 0.15,# Higher TF confirmation
        "sentiment": 0.10,      # News/calendar events
    })

    # Multi-timeframe confirmation requirements
    mtf_agreement_threshold: int = 2  # out of 3 timeframes must agree

    # Divergence detection sensitivity
    divergence_lookback: int = 14
    divergence_min_swing: float = 0.001  # minimum price swing for valid divergence

    # Signal cooldown (prevent over-signalling same direction)
    cooldown_bars: int = 5

    # Risk management defaults
    default_risk_pct: float = 1.0  # risk 1% per trade
    default_rr_ratio: float = 2.0  # 1:2 risk-reward minimum


@dataclass
class NewsConfig:
    """Economic calendar and sentiment configuration."""
    # High-impact event currencies
    tracked_currencies: List[str] = field(default_factory=lambda: [
        "USD", "EUR", "GBP", "JPY", "CHF", "AUD", "CAD", "NZD"
    ])

    # Event impact levels to monitor
    min_impact: str = "medium"  # "low", "medium", "high"

    # Pre-event buffer (minutes before high-impact event = no new signals)
    pre_event_buffer_minutes: int = 30

    # Post-event volatility window (minutes after event = cautious signals)
    post_event_buffer_minutes: int = 15

    # News sentiment sources
    rss_feeds: List[str] = field(default_factory=lambda: [
        "https://www.forexlive.com/feed/",
        "https://www.fxstreet.com/rss",
    ])


@dataclass
class PlatformConfig:
    """Overall platform configuration."""
    technical: TechnicalConfig = field(default_factory=TechnicalConfig)
    signals: SignalConfig = field(default_factory=SignalConfig)
    news: NewsConfig = field(default_factory=NewsConfig)

    # Default pairs to monitor
    watch_pairs: List[str] = field(default_factory=lambda: MAJOR_PAIRS)

    # Analysis timeframes (primary + confirmation)
    primary_timeframe: Timeframe = Timeframe.H1
    confirmation_timeframes: List[Timeframe] = field(
        default_factory=lambda: [Timeframe.M15, Timeframe.H4]
    )

    # Data source
    data_lookback_days: int = 60  # enough for 200 EMA on H1

    # Dashboard refresh interval (seconds)
    refresh_interval: int = 300  # 5 minutes

    # Logging
    log_level: str = "INFO"
    log_signals_to_file: bool = True
    signal_log_path: str = "signals.log"