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",
]

# Symbol display names
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",
}

# Pip values per symbol (used for trade setup risk/reward in pips)
# Forex defaults: 0.01 for JPY pairs, 0.0001 for everything else.
# Override here for any pair that doesn't follow that rule.
PIP_VALUES: Dict[str, float] = {}


@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)
    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

    # Divergence detection — how many bars back to scan for swing points
    divergence_lookback: int = 14


@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

    # 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.D1]
    )

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

    # Twelve Data API key (overridden by TWELVE_DATA_API_KEY env var)
    twelve_data_api_key: str = "f563b22ffdfd4924955decbe1a8c8701"

    # Dashboard refresh interval (seconds) — used as a fallback when a
    # timeframe isn't covered by cache_ttl_per_tf below.
    refresh_interval: int = 300  # 5 minutes

    # Per-timeframe cache TTL (seconds). A 1-week candle changes less
    # often than a 15-minute candle, so caching them all for the same
    # 5 minutes wastes API credits. Tuned to roughly match each TF's
    # bar interval so we re-fetch about once per new bar.
    cache_ttl_per_tf: Dict[Timeframe, int] = field(default_factory=lambda: {
        Timeframe.M1:  60,         # 1 minute
        Timeframe.M5:  150,        # 2.5 minutes
        Timeframe.M15: 300,        # 5 minutes
        Timeframe.M30: 600,        # 10 minutes
        Timeframe.H1:  1800,       # 30 minutes
        Timeframe.H4:  7200,       # 2 hours
        Timeframe.D1:  14400,      # 4 hours
        Timeframe.W1:  86400,      # 24 hours
    })

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