Files
ForexBot2/config.py
T
harwinder dad2432d4d Add M5 pullback entry archetype (XAU_PB): +140R combined on 12mo
Second entry pattern alongside the Keltner-breakout: enter on the
retrace to EMA21/KC-mid in an established trend (EMA >=3/4 aligned,
ADX>=20, retrace 0.8-6.0 ATR, resumption bar closed back in trend
direction, RSI in the pullback zone not the extended zone). Detector
lives in the aggregator so live and GPU-backtest paths share one
implementation. Own gates (composite floor 15, confirmation-TF
agreement, MTF opposition, vol regimes) with a diagnostic funnel.

PB stops anchor to the pullback swing (~$8 vs ~$25 breakout), so PB
trades get their own trail arm (0.8R vs 0.6R global) via per-trade
trail overrides in the backtester and strategy-aware Telegram alerts.

12mo M5 validation: PB alone +38.3R/254 trades, positive both halves
and all four full quarters; core breakout trades undisturbed
(+101.9R vs +105.0 baseline). Combined book: 549 trades (~10.6/wk),
+140.1R, PF 1.78, DD 11.3R vs 311 trades/+105.0R before.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-07-09 14:21:59 -04:00

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"""
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"
PAIR_INFO = {
XAUUSD: {"display": "XAU/USD", "pip_value": 0.10, "is_jpy_pair": False},
}
@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"])
min_impact: str = "medium"
pre_event_buffer_minutes: int = 30
post_event_buffer_minutes: int = 15
rss_feeds: List[str] = field(default_factory=lambda: [
"https://investinglive.com/feed/",
"https://www.fxstreet.com/rss",
])
@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"])
# ── 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 — see PULLBACK_ENTRY_PLAN.txt) ──
# 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 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)
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"