ForexBot2/config.py

"""
ForexBot2 — Configuration (XAU/USD focused)
==========================================
"""

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"


# ── Supported pairs ──────────────────────────────────────────────
XAUUSD = "XAU/USD"
EURUSD = "EUR/USD"

# price_precision: decimals for SL/TP rounding and display.
# default_spread: round-trip cost per trade in price units, charged by
# the backtester when --spread is not given.
PAIR_INFO = {
    XAUUSD: {"display": "XAU/USD", "pip_value": 0.10, "is_jpy_pair": False,
             "price_precision": 2, "default_spread": 0.30},
    EURUSD: {"display": "EUR/USD", "pip_value": 0.0001, "is_jpy_pair": False,
             "price_precision": 5, "default_spread": 0.0001},
}


@dataclass
class TechnicalConfig:
    """Technical indicator parameters."""
    ema_fast: int = 9
    ema_medium: int = 21
    ema_slow: int = 50
    ema_trend: int = 200

    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_fast: int = 12
    macd_slow: int = 26
    macd_signal: int = 9

    bb_period: int = 20
    bb_std: float = 2.0

    atr_period: int = 14

    adx_period: int = 14
    adx_strong_trend: float = 25.0
    adx_very_strong: float = 50.0

    divergence_lookback: int = 40
    swing_sr_lookback: int = 50

    disabled_indicators: List[str] = field(default_factory=list)

    ema_mode: str = "4ema"          # "4ema" (9/21/50/200) or "2ema" (50/200)
    rsi_mode: str = "regime_aware"  # "classic" or "regime_aware"
    macd_as_pillar: bool = True     # MACD histogram is a scored signal

    # ROC (Rate of Change)
    roc_period: int = 10
    roc_threshold: float = 1.0     # % threshold for strong signal

    # Keltner Channels
    kc_period: int = 20
    kc_atr_period: int = 10
    kc_multiplier: float = 1.5

    # ADX slope (trend acceleration detection)
    adx_slope_lookback: int = 5
    adx_slope_emerging_threshold: float = 3.0

    regime_weights_override: Dict[str, Dict[str, float]] = field(default_factory=dict)


@dataclass
class SignalConfig:
    """Signal scoring & filtering."""
    min_confidence: float = 55.0

    weights: Dict[str, float] = field(default_factory=lambda: {
        "ema_trend": 1.0,
        "rsi": 1.5,
        "bollinger": 1.5,
        "macd": 1.5,
        "keltner": 1.5,
        "roc": 1.5,
        "candlestick": 1.0,
        "divergence": 1.5,
    })

    mtf_agreement_threshold: int = 2  # of 3 timeframes
    cooldown_bars: int = 5

    default_risk_pct: float = 1.0
    default_rr_ratio: float = 2.0
    atr_sl_multiplier: float = 1.5
    min_rr_ratio: float = 0.5
    # TP tightening (May 2026) was tuned on the pre-spread backtester.
    # Re-tested 2026-07-08 with $0.30 spread + gap fills: 0.8 nearly
    # halves total R (+36.1R vs +66.8R, worse in both train/val halves)
    # — smaller wins make the fixed spread a larger share of every TP.
    tp_tightening_factor: float = 1.0

    # ── Trade geometry ────────────────────────────────────────────
    # Round-trip transaction cost estimate in price units (XAU ~$0.30).
    round_trip_cost: float = 0.30
    # Spread gate: reject setups whose TP1 distance is below
    # round_trip_cost × this multiple (caps cost at ~3% of target).
    # Validated 2026-07: small-target trades lose in both data halves
    # on M5 while TP≥$10 trades earn ~+0.08R/trade.
    min_tp_cost_multiple: float = 30.0
    # Fixed SL floor in pips (80 pips = $8 on XAU). 0 disables — SL then
    # floors at ATR × v2_sl_atr_multiplier only.
    min_sl_pips: float = 80.0
    # TP1 floor as a fraction of SL distance (0.5 = historical RR 0.5).
    tp_floor_rr: float = 0.5

    # ── Trailing-stop exit (2026-07) ──────────────────────────────
    # Once favorable excursion reaches trail_arm_r × risk, the stop
    # trails trail_dist_r × risk behind the best price (updated at bar
    # close). TP1 becomes advisory — the trail is the exit. Validated
    # on 12mo M5: +105R vs +48R with the fixed RR-0.5 target, balanced
    # train/val, positive every quarter, PF 2.27. The RR-0.5 target was
    # the binding constraint — winners kept running after TP.
    # Set trail_arm_r = 0 to disable and exit at TP1 as before.
    trail_arm_r: float = 0.6
    trail_dist_r: float = 0.75
    # Pullback (XAU_PB) trades run tighter stops (~$8 vs ~$25), so the
    # global 0.6R arm fires on noise. Arm later; whole 0.8-arm row of
    # the grid is +35-38R vs +32R at global params (balanced halves).
    pb_trail_arm_r: float = 0.8
    pb_trail_dist_r: float = 0.75


@dataclass
class NewsConfig:
    """Economic calendar & sentiment."""
    tracked_currencies: List[str] = field(default_factory=lambda: ["USD", "XAU", "EUR"])
    pre_event_buffer_minutes: int = 30
    post_event_buffer_minutes: int = 15
    # Whether event risk gates the SIGNAL (danger: confidence hard-capped
    # at 30; caution: 15-point penalty). Warnings are always emitted
    # regardless. Default False = XAU-tuned: replaying the live gates
    # against the validated 12mo XAU M5 book (547 trades, +139.9R)
    # showed they suppress 25-35 trades worth +4.6..+7.2R/yr — trades
    # entered near USD releases OUTPERFORM (+0.475R vs +0.256R avg).
    # Audit 2026-07-11 via backtest/research/calendar_store.
    event_risk_caps_signals: bool = False
    # Wider stay-out window after a high-impact release that surprised
    # vs forecast (inline releases use post_event_buffer_minutes).
    post_event_surprise_buffer_minutes: int = 45
    # How long fetched calendar/headline data is reused across scans.
    # Must stay below pre_event_buffer_minutes so an event can't cross
    # into the danger window while a stale cache says it's clear.
    context_cache_ttl_seconds: int = 600

    rss_feeds: List[str] = field(default_factory=lambda: [
        "https://investinglive.com/feed/",
        "https://www.fxstreet.com/rss",
        # Google News query targeted at gold drivers — also carries Kitco,
        # Reuters etc. whose direct feeds are unavailable.
        "https://news.google.com/rss/search?q=gold+price+OR+fed+OR+inflation&hl=en-US&gl=US&ceid=US:en",
        # CNBC "Economy" section
        "https://search.cnbc.com/rs/search/combinedcms/view.xml?partnerId=wrss01&id=20910258",
    ])


@dataclass
class XauStrategyConfig:
    """XAU/USD strategy config.
    Legacy gates (H4 RSI, H1 MACD, M15 score) removed in favor of
    new momentum indicators (ROC, Keltner squeeze, ADX slope).
    """
    enabled: bool = True
    rsi_entry_threshold: float = 45.0
    tp_atr_multiplier: float = 1.0
    sl_atr_multiplier: float = 2.0
    min_ema200_tfs: int = 2
    allow_generic_trades: bool = True
    blocked_hours_utc: List[int] = field(default_factory=lambda: [0, 1, 2, 10, 11, 13, 16, 21])
    weekend_filter: bool = True
    min_atr_threshold: float = 1.0
    v2_sl_atr_multiplier: float = 2.0
    buy_threshold_boost: int = 0
    m5_confirmation_bars: int = 0
    h4_rsi_gate: bool = False
    h1_macd_gate: bool = False
    rsi_zone: tuple = (40.0, 65.0)
    allowed_weekdays: List[int] = field(default_factory=lambda: [0, 1, 2, 3, 4, 6])  # Mon-Fri + Sun (Sydney open)
    sell_min_quality: List[str] = field(default_factory=lambda: ["A+", "A", "B"])
    # Volatility regimes in which SELL setups are allowed (low/normal-vol
    # shorts lose consistently against gold's macro uptrend).
    sell_vol_regimes: List[str] = field(default_factory=lambda: ["high", "extreme"])
    # Market regimes in which no XAU setup may fire (any direction).
    # Empty by default; per-timeframe factories opt in — e.g. the mixed
    # "trending" regime (strong ADX, EMAs disagree) on M15.
    blocked_regimes: List[str] = field(default_factory=list)
    # Market regimes in which XAU SELL setups may not fire. Empty by
    # default; per-timeframe factories opt in.
    sell_blocked_regimes: List[str] = field(default_factory=list)
    # Bar-CLOSE (decision-time) UTC hours in which XAU SELL setups may
    # not fire. Empty by default; per-timeframe factories opt in.
    # BUYs are unaffected (unlike blocked_hours_utc, which is both-way).
    sell_blocked_hours_utc: List[int] = field(default_factory=list)

    # ── M5-specific filters ──────────────────────────────────────
    # M5 signals are noisy; require stronger confirmation before
    # generating trade setups. Without these, M5 is breakeven
    # (+0.01R/trade) with 21% drawdown.
    m5_require_mtf: bool = True
    m5_min_abs_score: float = 30.0
    m5_min_confirmation_score: float = 10.0
    # A-grade M5 SELLs enter at the extreme of temporary dips and
    # lose (-0.017R/trade on 163 trades) — maximum conviction at
    # the worst entry. Cap SELL quality so A-grade can't trigger
    # the ATR-based setup generator; B-grade swing setups survive
    # because they catch moderate drops, not extremes.
    m5_sell_max_quality: List[str] = field(default_factory=lambda: ["B", "C"])
    # 'high' vol regime on M5 is chop transition — elevated noise
    # without directional expansion. 61% WR / negative total across
    # 12mo while low/normal/extreme are all positive (validated 2026-07).
    m5_blocked_vol_regimes: List[str] = field(default_factory=lambda: ["high"])
    # Block M5 SELLs when RSI is already < this floor: the dip is
    # extended and mean-reverts before the target (negative in both
    # halves of 6mo and 12mo backtests).
    m5_sell_min_rsi: float = 25.0

    # ── M5 pullback entry (XAU_PB) ──
    # Second entry archetype: enter on the retrace to EMA21/KC-mid in
    # an established trend instead of at Keltner-breakout extension.
    # Validated 2026-07: +38.3R/254 trades on 12mo, positive both
    # halves and all four full quarters, core trades undisturbed.
    m5_pullback_enabled: bool = True
    # Composite score is weaker mid-pullback BY DESIGN (price sits
    # below the momentum bands) — separate, lower floor than Gate 1.
    m5_pullback_min_score: float = 15.0
    m5_pullback_adx_min: float = 20.0
    # RSI must be in the pullback zone, NOT the extended zone the
    # breakout entries fire in (those run 65-80).
    m5_pullback_rsi_buy: tuple = (35.0, 62.0)
    m5_pullback_rsi_sell: tuple = (38.0, 65.0)
    # Retrace depth from the pre-pullback swing extreme, in ATRs.
    # Shallower = still extended; deeper = trend likely broken.
    # M5 gold trend legs measure 3-4 ATR swing-to-trough (median 3.9),
    # so the ceiling sits well above that of higher TFs.
    m5_pullback_retrace_atr: tuple = (0.8, 6.0)
    # Price must have touched EMA21/KC-mid within this many bars.
    m5_pullback_touch_bars: int = 3


@dataclass
class EurUsdStrategyConfig:
    """EUR/USD strategy config — separate from XAU for independent tuning.

    Values ported from feature/eurusd-support are a pre-realism baseline
    (tuned before spread charging and next-open fills) and are re-tuned
    against the realistic backtester. Cost knobs (round_trip_cost,
    min_tp_cost_multiple, min_sl_pips) are EUR-local so nothing
    gold-calibrated from SignalConfig leaks into the EUR path.
    """
    enabled: bool = True
    blocked_hours_utc: List[int] = field(default_factory=lambda: [22, 23, 0, 1, 2, 3])
    weekend_filter: bool = True
    allowed_weekdays: List[int] = field(default_factory=lambda: [0, 1, 2, 3, 4])
    min_atr_threshold: float = 0.0003
    sl_atr_multiplier: float = 1.5     # swing-buffer ATR multiple for SL placement
    tp_atr_multiplier: float = 1.2

    sl_atr_floor: float = 1.2
    min_rr_ratio: float = 1.0
    mature_move_threshold: float = 35.0
    tp_quality_scale: Dict[str, float] = field(default_factory=lambda: {
        "A+": 1.0, "A": 1.0, "B": 1.0, "C": 1.0,
    })
    blocked_regimes: List[str] = field(default_factory=lambda: ["ranging", "transitioning"])
    min_quality_grades: List[str] = field(default_factory=lambda: ["A+", "A", "B"])
    max_exhaustion_tags: int = 99
    block_near_ema200: bool = False
    session_hours: List[int] = field(default_factory=list)
    min_entry_score: float = 38.0
    min_entry_confidence: float = 60.0
    block_rsi_extended: bool = True
    blocked_vol_regimes: List[str] = field(default_factory=list)
    min_indicator_agreement: int = 0
    be_trigger_r: float = 0.3
    be_buffer_r: float = 0.15

    # ── EUR-local trade-cost knobs (replace SignalConfig's gold-dollar
    # values in the EUR path) ─────────────────────────────────────────
    # Round-trip cost per trade in price units (1.0 pip).
    round_trip_cost: float = 0.0001
    # Reject setups whose TP1 distance < round_trip_cost × this multiple
    # (10 → 10-pip minimum target; EUR M5 ATR runs ~5-8 pips).
    min_tp_cost_multiple: float = 10.0
    # Minimum SL distance in pips.
    min_sl_pips: float = 8.0


@dataclass
class FilterConfig:
    """Regime and session filters for live signals."""
    regime_filter: bool = False
    regime_filter_timeframe: Timeframe = Timeframe.H4
    regime_filter_min_adx: float = 25.0

    session_filter: bool = True
    session_start_hour: int = 3
    session_end_hour: int = 23
    blocked_hours_utc: List[int] = field(default_factory=lambda: [0, 1, 2, 10, 11, 13, 16, 21])

    allowed_weekdays: List[int] = field(default_factory=lambda: [0, 1, 2, 3, 4, 6])  # Mon-Fri + Sun (Sydney open)


@dataclass
class PlatformConfig:
    """Top-level configuration."""
    technical: TechnicalConfig = field(default_factory=TechnicalConfig)
    signals: SignalConfig = field(default_factory=SignalConfig)
    news: NewsConfig = field(default_factory=NewsConfig)
    backtest: FilterConfig = field(default_factory=FilterConfig)
    xau_strategy: XauStrategyConfig = field(default_factory=XauStrategyConfig)
    eur_strategy: EurUsdStrategyConfig = field(default_factory=EurUsdStrategyConfig)

    symbol: str = XAUUSD
    display_name: str = "XAU/USD"
    pip_value: float = 0.10

    primary_timeframe: Timeframe = Timeframe.H1
    confirmation_timeframes: List[Timeframe] = field(
        default_factory=lambda: [Timeframe.M15, Timeframe.H4]
    )

    data_lookback_days: int = 60

    twelve_data_api_key: str = "f563b22ffdfd4924955decbe1a8c8701"

    refresh_interval: int = 300

    scan_pairs: List[str] = field(
        default_factory=lambda: [XAUUSD]
    )
    scan_timeframes: List[Timeframe] = field(
        default_factory=lambda: [Timeframe.M5, Timeframe.M15, Timeframe.H1, Timeframe.H4]
    )
    candle_buffer_seconds: int = 10
    ws_cooldown_seconds: int = 300

    log_level: str = "INFO"