harwinder
bb3c475f22
Signal daemon (signal_web.py): candle-boundary scanner mirroring telegram_bot.py, publishes serialized SignalReport JSON to Redis. Web API (web/app.py): thin FastAPI reader behind Apache, serves /api/signals REST + /ws WebSocket from Redis pub/sub. Frontend (web/static/index.html): 3-pair grid, color-coded signals, indicator breakdown per timeframe, trade setup display. Also: XAU-specific penalty scoping in signal_aggregator (softer confidence penalties for gold, original strict values for forex), pair-aware session filter routing XAU to its own blocked hours.
1366 lines
57 KiB
Python
Executable File
1366 lines
57 KiB
Python
Executable File
"""
|
||
ForexBot2 — Signal Aggregator
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||
==============================
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||
Combines multi-timeframe technical analysis with optional news context
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into a graded actionable signal.
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"""
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||
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import logging
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import os
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||
from dataclasses import dataclass, field
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from datetime import datetime, timezone
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from typing import Dict, List, Optional
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||
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import pandas as pd
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||
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from config import PlatformConfig, SignalStrength, Timeframe
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from data_provider import ForexDataProvider
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from engine import TechnicalEngine, TechnicalAnalysis
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from news_engine import NewsEngine, FundamentalContext
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logger = logging.getLogger(__name__)
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@dataclass
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class TradeSetup:
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pair: str
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display_name: str
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direction: str # "BUY" / "SELL"
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entry_price: float
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stop_loss: float
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take_profit_1: float
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take_profit_2: float
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risk_reward: float
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risk_pips: float
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reward_pips: float
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pip_value: float
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@dataclass
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class SignalReport:
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symbol: str
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display_name: str
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timestamp: str
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primary_signal: SignalStrength = SignalStrength.NEUTRAL
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primary_score: float = 0.0
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primary_confidence: float = 0.0
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mtf_agreement: bool = False
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mtf_signals: Dict[str, SignalStrength] = field(default_factory=dict)
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mtf_scores: Dict[str, float] = field(default_factory=dict)
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primary_analysis: Optional[TechnicalAnalysis] = None
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confirmation_analyses: List[TechnicalAnalysis] = field(default_factory=list)
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event_risk: str = "clear"
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event_description: str = ""
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news_sentiment: float = 0.0
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news_description: str = ""
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final_signal: SignalStrength = SignalStrength.NEUTRAL
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final_score: float = 0.0
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final_confidence: float = 0.0
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action_recommendation: str = ""
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signal_quality: str = "" # A+, A, B, C, D, F
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trade_setup: Optional[TradeSetup] = None
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bullish_reasons: List[str] = field(default_factory=list)
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bearish_reasons: List[str] = field(default_factory=list)
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warnings: List[str] = field(default_factory=list)
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current_price: float = 0.0
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spread_estimate: float = 0.0
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market_regime: str = ""
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volatility_regime: str = ""
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class SignalAggregator:
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"""Master aggregator for live signal analysis."""
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def __init__(self, config: PlatformConfig):
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self.config = config
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self.data_provider = ForexDataProvider(config)
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self.tech_engine = TechnicalEngine(config.technical)
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self._news_engine: Optional[NewsEngine] = None # lazy
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def _get_news_engine(self) -> NewsEngine:
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if self._news_engine is None:
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self._news_engine = NewsEngine(self.config.news)
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return self._news_engine
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# ── Public: live mode entry point ──────────────────────────────
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def analyze_pair(
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self,
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symbol: Optional[str] = None,
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context: Optional[FundamentalContext] = None,
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) -> SignalReport:
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"""Live-mode entry: fetch all needed timeframes then delegate."""
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if symbol is None:
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symbol = self.config.symbol
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pair_info = self.data_provider.get_pair_info(symbol)
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now_utc = datetime.now(timezone.utc)
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if pair_info["display"] == "XAU/USD" and self.config.xau_strategy.enabled:
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xau_cfg = self.config.xau_strategy
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if xau_cfg.weekend_filter and now_utc.weekday() >= 5:
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report = SignalReport(
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symbol=symbol,
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display_name=pair_info["display"],
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timestamp=str(now_utc),
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)
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report.final_signal = SignalStrength.NEUTRAL
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report.signal_quality = "F"
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report.trade_setup = None
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report.warnings.append("WEEKEND FILTER: XAU/USD market closed — no liquidity")
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report.action_recommendation = "NO TRADE — Weekend (market closed)"
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return report
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if xau_cfg.allowed_weekdays and now_utc.weekday() not in xau_cfg.allowed_weekdays:
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day_names = {0: "Mon", 1: "Tue", 2: "Wed", 3: "Thu", 4: "Fri"}
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allowed = "/".join(day_names.get(d, str(d)) for d in xau_cfg.allowed_weekdays)
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report = SignalReport(
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symbol=symbol,
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display_name=pair_info["display"],
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timestamp=str(now_utc),
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)
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report.final_signal = SignalStrength.NEUTRAL
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report.signal_quality = "F"
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report.trade_setup = None
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report.warnings.append(
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f"DAY FILTER: {day_names.get(now_utc.weekday(), '?')} not in allowed days ({allowed})"
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)
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report.action_recommendation = f"NO TRADE — Only trading {allowed}"
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return report
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timeframes = [self.config.primary_timeframe] + list(
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self.config.confirmation_timeframes
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)
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bt = self.config.backtest
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if bt.regime_filter and bt.regime_filter_timeframe not in timeframes:
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timeframes.append(bt.regime_filter_timeframe)
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dfs: Dict[Timeframe, pd.DataFrame] = {}
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stale_tfs = []
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for tf in timeframes:
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try:
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df = self.data_provider.fetch_ohlcv(symbol, tf)
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dfs[tf] = df
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if not self.data_provider._is_data_fresh(df, symbol, tf):
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stale_tfs.append(tf.value)
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except Exception as e:
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logger.warning(f"Fetch failed for {symbol} {tf.value}: {e}")
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report = self.analyze_from_dataframes(
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symbol=symbol,
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dfs=dfs,
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context=context,
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use_news=True,
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)
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if stale_tfs:
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report.warnings.append(f"STALE DATA on {', '.join(stale_tfs)} — signal may be unreliable")
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if self.config.primary_timeframe.value in stale_tfs:
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report.final_signal = SignalStrength.NEUTRAL
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report.signal_quality = "F"
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report.trade_setup = None
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report.warnings.append("Primary timeframe stale — signal suppressed")
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if bt.regime_filter:
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self._apply_regime_filter_live(report, dfs)
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if bt.session_filter:
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xau_active = (
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report.display_name == "XAU/USD"
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and self.config.xau_strategy.enabled
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and any("XAU STRATEGY" in r for r in report.bullish_reasons)
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)
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eur_active = (
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report.display_name == "EUR/USD"
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and self.config.eur_strategy.enabled
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and any("EUR STRATEGY" in r for r in report.bullish_reasons)
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)
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gbp_active = (
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report.display_name == "GBP/USD"
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and self.config.gbp_strategy.enabled
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and any("GBP STRATEGY" in r for r in report.bullish_reasons)
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)
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if not xau_active and not eur_active and not gbp_active:
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self._apply_session_filter_live(report)
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return report
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def _apply_session_filter_live(self, report: SignalReport) -> None:
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"""Skip signals outside the configured UTC trading window."""
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bt = self.config.backtest
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now_h = datetime.now(timezone.utc).hour
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if not (bt.session_start_hour <= now_h < bt.session_end_hour):
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report.warnings.append(
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f"SESSION FILTER: {now_h:02}:00 UTC outside "
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f"{bt.session_start_hour:02}:00-{bt.session_end_hour:02}:00 — skipping"
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)
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report.final_signal = SignalStrength.NEUTRAL
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report.signal_quality = "F"
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report.action_recommendation = (
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f"NO TRADE — Outside session "
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f"({bt.session_start_hour:02}-{bt.session_end_hour:02} UTC; now {now_h:02})"
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)
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report.trade_setup = None
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else:
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report.warnings.append(
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f"Session: {now_h:02}:00 UTC inside trading window "
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f"{bt.session_start_hour:02}-{bt.session_end_hour:02}"
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)
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def _apply_regime_filter_live(
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self, report: SignalReport, dfs: Dict[Timeframe, pd.DataFrame]
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) -> None:
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"""If higher-TF ADX is below threshold, downgrade signal to NEUTRAL."""
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bt = self.config.backtest
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regime_tf = bt.regime_filter_timeframe
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df = dfs.get(regime_tf)
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if df is None or df.empty:
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report.warnings.append(
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f"Regime filter requested but {regime_tf.value} data unavailable"
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)
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return
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adx_value = self._latest_adx(df, self.config.technical.adx_period)
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if adx_value is None:
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report.warnings.append(
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f"Regime filter: ADX could not be computed on {regime_tf.value}"
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)
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return
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if adx_value < bt.regime_filter_min_adx:
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report.warnings.append(
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f"REGIME FILTER: {regime_tf.value} ADX={adx_value:.1f} < "
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f"{bt.regime_filter_min_adx:.0f} — market choppy, skipping signal"
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)
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report.final_signal = SignalStrength.NEUTRAL
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report.signal_quality = "F"
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report.action_recommendation = (
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f"NO TRADE — Regime filter (ADX {adx_value:.1f} on {regime_tf.value})"
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)
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report.trade_setup = None
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else:
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report.bullish_reasons.append(
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f"Regime: {regime_tf.value} ADX={adx_value:.1f} confirms trending market"
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) if report.final_score > 0 else report.bearish_reasons.append(
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f"Regime: {regime_tf.value} ADX={adx_value:.1f} confirms trending market"
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)
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@staticmethod
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def _latest_adx(df: pd.DataFrame, period: int = 14) -> Optional[float]:
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"""Wilder ADX on a fresh df; returns the last finite value or None."""
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if df is None or len(df) < period * 3:
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return None
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high, low, close = df["High"], df["Low"], df["Close"]
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tr = pd.concat([
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high - low,
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(high - close.shift()).abs(),
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(low - close.shift()).abs(),
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], axis=1).max(axis=1)
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plus_dm = high.diff()
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minus_dm = -low.diff()
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plus_dm = plus_dm.where((plus_dm > minus_dm) & (plus_dm > 0), 0.0)
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minus_dm = minus_dm.where((minus_dm > plus_dm) & (minus_dm > 0), 0.0)
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atr_s = tr.ewm(alpha=1/period, min_periods=period, adjust=False).mean()
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plus_di = 100 * (plus_dm.ewm(alpha=1/period, min_periods=period, adjust=False).mean() / atr_s)
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minus_di = 100 * (minus_dm.ewm(alpha=1/period, min_periods=period, adjust=False).mean() / atr_s)
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denom = (plus_di + minus_di).replace(0, float("nan"))
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dx = 100 * (plus_di - minus_di).abs() / denom
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adx = dx.ewm(alpha=1/period, min_periods=period, adjust=False).mean().dropna()
|
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if adx.empty:
|
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return None
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||
return float(adx.iloc[-1])
|
||
|
||
# ── Public: bar-replayable entry point ─────────────────────────
|
||
|
||
def analyze_from_dataframes(
|
||
self,
|
||
symbol: str,
|
||
dfs: Dict[Timeframe, pd.DataFrame],
|
||
context: Optional[FundamentalContext] = None,
|
||
use_news: bool = True,
|
||
) -> SignalReport:
|
||
"""
|
||
Run the full analysis pipeline on already-fetched dataframes.
|
||
|
||
`dfs` must include the primary timeframe and ideally the
|
||
confirmation timeframes. Each df is treated as the visible history
|
||
at decision time — the backtester is responsible for slicing so
|
||
no future bars leak in.
|
||
"""
|
||
pair_info = self.data_provider.get_pair_info(symbol)
|
||
display = pair_info["display"]
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||
pip_value = pair_info["pip_value"]
|
||
|
||
report = SignalReport(
|
||
symbol=symbol,
|
||
display_name=display,
|
||
timestamp=str(datetime.now(timezone.utc)),
|
||
)
|
||
|
||
# ── 1. Primary timeframe ───────────────────────────────────
|
||
primary_df = dfs.get(self.config.primary_timeframe)
|
||
if primary_df is None or primary_df.empty:
|
||
report.warnings.append("Primary timeframe data unavailable")
|
||
report.signal_quality = "F"
|
||
return report
|
||
|
||
primary_analysis = self.tech_engine.analyze(
|
||
primary_df, symbol, self.config.primary_timeframe.value
|
||
)
|
||
report.primary_analysis = primary_analysis
|
||
report.primary_signal = primary_analysis.composite_signal
|
||
report.primary_score = primary_analysis.composite_score
|
||
report.primary_confidence = primary_analysis.confidence
|
||
report.market_regime = primary_analysis.market_regime
|
||
report.volatility_regime = primary_analysis.volatility_regime
|
||
report.current_price = float(primary_df["Close"].iloc[-1])
|
||
report.timestamp = str(primary_df.index[-1])
|
||
report.mtf_signals[self.config.primary_timeframe.value] = primary_analysis.composite_signal
|
||
report.mtf_scores[self.config.primary_timeframe.value] = primary_analysis.composite_score
|
||
|
||
# ── 2. Confirmation timeframes ─────────────────────────────
|
||
for tf in self.config.confirmation_timeframes:
|
||
cf_df = dfs.get(tf)
|
||
if cf_df is None or cf_df.empty:
|
||
continue
|
||
try:
|
||
cf_analysis = self.tech_engine.analyze(cf_df, symbol, tf.value)
|
||
report.confirmation_analyses.append(cf_analysis)
|
||
report.mtf_signals[tf.value] = cf_analysis.composite_signal
|
||
report.mtf_scores[tf.value] = cf_analysis.composite_score
|
||
except Exception as e:
|
||
logger.warning(f"Confirmation TF {tf.value} failed for {symbol}: {e}")
|
||
|
||
# ── 3. MTF agreement ───────────────────────────────────────
|
||
report.mtf_agreement = self._check_mtf_agreement(report)
|
||
|
||
# ── 4. Fundamental context (optional) ──────────────────────
|
||
if use_news:
|
||
news = self._get_news_engine()
|
||
if context is None:
|
||
context = news.get_fundamental_context()
|
||
event_risk, event_desc = news.get_event_risk_level(symbol, context)
|
||
report.event_risk = event_risk
|
||
report.event_description = event_desc
|
||
sentiment, sent_desc = news.get_pair_sentiment(symbol, context)
|
||
report.news_sentiment = sentiment
|
||
report.news_description = sent_desc
|
||
else:
|
||
report.event_risk = "clear"
|
||
report.event_description = ""
|
||
report.news_sentiment = 0.0
|
||
report.news_description = ""
|
||
|
||
# ── 5. Spread estimate from primary data (avoids extra API call) ─
|
||
try:
|
||
report.spread_estimate = float(
|
||
(primary_df["High"] - primary_df["Low"]).median()
|
||
)
|
||
except Exception:
|
||
report.spread_estimate = 0.0
|
||
|
||
# ── 6. Final signal ────────────────────────────────────────
|
||
self._compute_final_signal(report)
|
||
|
||
# ── 6b. Session filter (works for both live and backtest) ─
|
||
if self.config.backtest.session_filter:
|
||
try:
|
||
bar_ts = pd.Timestamp(report.timestamp)
|
||
bar_hour = bar_ts.hour
|
||
bar_wd = bar_ts.weekday()
|
||
_is_xau_pair = report.display_name == "XAU/USD"
|
||
_blocked_hours = (self.config.xau_strategy.blocked_hours_utc
|
||
if _is_xau_pair else self.config.backtest.blocked_hours_utc)
|
||
if bar_hour in _blocked_hours:
|
||
report.final_signal = SignalStrength.NEUTRAL
|
||
report.signal_quality = "F"
|
||
report.warnings.append(f"SESSION FILTER: {bar_hour:02}:00 UTC blocked")
|
||
_allowed_wd = (self.config.xau_strategy.allowed_weekdays
|
||
if _is_xau_pair else self.config.backtest.allowed_weekdays)
|
||
if _allowed_wd and bar_wd not in _allowed_wd:
|
||
day_names = {0: "Mon", 1: "Tue", 2: "Wed", 3: "Thu",
|
||
4: "Fri", 5: "Sat", 6: "Sun"}
|
||
report.final_signal = SignalStrength.NEUTRAL
|
||
report.signal_quality = "F"
|
||
report.warnings.append(
|
||
f"DAY FILTER: {day_names.get(bar_wd, '?')} not in allowed days"
|
||
)
|
||
except Exception:
|
||
pass
|
||
|
||
# ── 6c. XAU/USD oversold bounce strategy (DISABLED — replaced by v2 confluence) ──
|
||
# if report.display_name == "XAU/USD" and self.config.xau_strategy.enabled:
|
||
# if self._check_xau_oversold_bounce(report, dfs):
|
||
# report.final_signal = SignalStrength.STRONG_BUY
|
||
# report.final_score = 50.0
|
||
# report.final_confidence = 85.0
|
||
# report.signal_quality = "A+"
|
||
# report.action_recommendation = (
|
||
# "STRONG BUY — XAU oversold bounce "
|
||
# "(RSI<30 + M15/H1/H4 all above EMA200)"
|
||
# )
|
||
# report.bullish_reasons.insert(
|
||
# 0,
|
||
# "XAU STRATEGY: M15 RSI oversold + triple-TF bullish trend confirmation",
|
||
# )
|
||
# report.trade_setup = self._generate_xau_trade_setup(report, dfs)
|
||
|
||
# ── 6d. EUR/USD pullback-buy strategy ─────────────────────
|
||
if report.display_name == "EUR/USD" and self.config.eur_strategy.enabled:
|
||
if self._check_eur_pullback_buy(report, dfs):
|
||
report.final_signal = SignalStrength.BUY
|
||
report.final_score = 40.0
|
||
report.final_confidence = 75.0
|
||
report.signal_quality = "A"
|
||
report.action_recommendation = (
|
||
"BUY — EUR pullback entry "
|
||
"(RSI pullback + not at resistance + M15/H1 above EMA200)"
|
||
)
|
||
report.bullish_reasons.insert(
|
||
0,
|
||
"EUR STRATEGY: M15 RSI pullback + BB mid-band + dual-TF EMA200 confirmation",
|
||
)
|
||
report.trade_setup = self._generate_eur_trade_setup(report, dfs)
|
||
|
||
# ── 6e. GBP/USD pullback-buy strategy ─────────────────────
|
||
if report.display_name == "GBP/USD" and self.config.gbp_strategy.enabled:
|
||
if self._check_gbp_pullback_buy(report, dfs):
|
||
report.final_signal = SignalStrength.BUY
|
||
report.final_score = 40.0
|
||
report.final_confidence = 75.0
|
||
report.signal_quality = "A"
|
||
report.action_recommendation = (
|
||
"BUY — GBP pullback entry "
|
||
"(RSI pullback + not at resistance + M15/H1 above EMA200)"
|
||
)
|
||
report.bullish_reasons.insert(
|
||
0,
|
||
"GBP STRATEGY: M15 RSI pullback + BB mid-band + dual-TF EMA200 confirmation",
|
||
)
|
||
report.trade_setup = self._generate_gbp_trade_setup(report, dfs)
|
||
|
||
# ── 6d. XAU/USD BUY threshold boost (Fix 5) ──────────────
|
||
if (report.display_name == "XAU/USD"
|
||
and self.config.xau_strategy.buy_threshold_boost > 0
|
||
and report.final_signal in (SignalStrength.BUY, SignalStrength.STRONG_BUY)
|
||
and report.signal_quality in ("B", "C")):
|
||
report.warnings.append(
|
||
f"XAU BUY FILTER: BUY requires higher confidence (quality {report.signal_quality} insufficient)"
|
||
)
|
||
report.signal_quality = "D"
|
||
report.trade_setup = None
|
||
|
||
# ── 6f. XAU/USD H4 RSI + H1 MACD directional gates ──────
|
||
if (report.display_name == "XAU/USD"
|
||
and self.config.xau_strategy.enabled
|
||
and report.signal_quality in ("A+", "A", "B", "C")
|
||
and report.final_signal != SignalStrength.NEUTRAL):
|
||
xau_cfg = self.config.xau_strategy
|
||
is_buy = report.final_signal in (SignalStrength.BUY, SignalStrength.STRONG_BUY)
|
||
|
||
if xau_cfg.h4_rsi_gate and Timeframe.H4 in dfs:
|
||
h4_close = dfs[Timeframe.H4]["Close"]
|
||
delta = h4_close.diff()
|
||
gain = delta.clip(lower=0).ewm(alpha=1/14, min_periods=14, adjust=False).mean()
|
||
loss = (-delta.clip(upper=0)).ewm(alpha=1/14, min_periods=14, adjust=False).mean()
|
||
h4_rsi = 100 - (100 / (1 + gain / loss))
|
||
if len(h4_rsi) > 0:
|
||
h4_rsi_val = float(h4_rsi.iloc[-1])
|
||
if is_buy and h4_rsi_val <= 55:
|
||
report.warnings.append(
|
||
f"H4 RSI GATE: RSI {h4_rsi_val:.0f} ≤55 — no BUY confirmation"
|
||
)
|
||
report.signal_quality = "D"
|
||
report.trade_setup = None
|
||
elif not is_buy and h4_rsi_val >= 45:
|
||
report.warnings.append(
|
||
f"H4 RSI GATE: RSI {h4_rsi_val:.0f} ≥45 — no SELL confirmation"
|
||
)
|
||
report.signal_quality = "D"
|
||
report.trade_setup = None
|
||
|
||
if (xau_cfg.h1_macd_gate
|
||
and Timeframe.H1 in dfs
|
||
and report.signal_quality in ("A+", "A", "B", "C")):
|
||
h1_df = dfs[Timeframe.H1]
|
||
h1_close = h1_df["Close"]
|
||
h1_ema_fast = h1_close.ewm(span=12, adjust=False).mean()
|
||
h1_ema_slow = h1_close.ewm(span=26, adjust=False).mean()
|
||
h1_macd_line = h1_ema_fast - h1_ema_slow
|
||
h1_signal_line = h1_macd_line.ewm(span=9, adjust=False).mean()
|
||
h1_macd_hist = h1_macd_line - h1_signal_line
|
||
if len(h1_macd_hist) > 0:
|
||
h1_hist_val = float(h1_macd_hist.iloc[-1])
|
||
if is_buy and h1_hist_val <= 0:
|
||
report.warnings.append(
|
||
f"H1 MACD GATE: histogram {h1_hist_val:.2f} ≤0 — no BUY confirmation"
|
||
)
|
||
report.signal_quality = "D"
|
||
report.trade_setup = None
|
||
elif not is_buy and h1_hist_val >= 0:
|
||
report.warnings.append(
|
||
f"H1 MACD GATE: histogram {h1_hist_val:.2f} ≥0 — no SELL confirmation"
|
||
)
|
||
report.signal_quality = "D"
|
||
report.trade_setup = None
|
||
|
||
# ── RSI zone gate ──────────────────────────────────────
|
||
if (xau_cfg.rsi_zone
|
||
and report.signal_quality in ("A+", "A", "B", "C")):
|
||
m15_analysis = report.primary_analysis
|
||
if m15_analysis and hasattr(m15_analysis, '_rsi_series'):
|
||
rsi_val = float(m15_analysis._rsi_series.iloc[-1])
|
||
lo, hi = xau_cfg.rsi_zone
|
||
if not (lo <= rsi_val <= hi):
|
||
report.warnings.append(
|
||
f"RSI ZONE GATE: RSI {rsi_val:.0f} outside [{lo:.0f}-{hi:.0f}]"
|
||
)
|
||
report.signal_quality = "D"
|
||
report.trade_setup = None
|
||
|
||
# ── 6g. XAU/USD SELL quality gate ─────────────────────────
|
||
xau_is_sell_dir = (
|
||
report.final_signal in (SignalStrength.SELL, SignalStrength.STRONG_SELL)
|
||
or (report.final_signal == SignalStrength.NEUTRAL and report.final_score < 0)
|
||
)
|
||
if (report.display_name == "XAU/USD"
|
||
and self.config.xau_strategy.enabled
|
||
and xau_is_sell_dir
|
||
and report.signal_quality not in self.config.xau_strategy.sell_min_quality):
|
||
report.warnings.append(
|
||
f"XAU SELL FILTER: quality {report.signal_quality} below minimum for SELL"
|
||
)
|
||
report.signal_quality = "D"
|
||
report.trade_setup = None
|
||
|
||
# ── 7. Trade setup for actionable signals ──────────────────
|
||
# Pair-specific generic-trade suppression: when a pair has a dedicated
|
||
# strategy and that strategy didn't fire, falling through to a generic
|
||
# swing-based setup tends to chase momentum at unfavorable spots.
|
||
# 90-day EUR M15 backtest: allow=True → +4.7R, allow=False → +9.5R.
|
||
suppress_generic = (
|
||
(report.display_name == "XAU/USD"
|
||
and not self.config.xau_strategy.allow_generic_trades)
|
||
or (report.display_name == "EUR/USD"
|
||
and self.config.eur_strategy.enabled
|
||
and not self.config.eur_strategy.allow_generic_trades)
|
||
or (report.display_name == "GBP/USD"
|
||
and self.config.gbp_strategy.enabled
|
||
and not self.config.gbp_strategy.allow_generic_trades)
|
||
)
|
||
if report.trade_setup is None and suppress_generic:
|
||
pass # generic trade setup suppressed for this pair
|
||
elif report.trade_setup is None and report.signal_quality in ("A+", "A", "B", "C"):
|
||
is_sell_direction = (
|
||
report.final_signal in (SignalStrength.SELL, SignalStrength.STRONG_SELL)
|
||
or (report.final_signal == SignalStrength.NEUTRAL and report.final_score < 0)
|
||
)
|
||
if is_sell_direction and self.config.backtest.sell_filter:
|
||
if report.display_name in self.config.backtest.sell_allowed_pairs:
|
||
report.trade_setup = self._generate_trade_setup(report, pip_value)
|
||
elif self._forex_sell_qualifies(report):
|
||
report.trade_setup = self._generate_trade_setup(report, pip_value)
|
||
else:
|
||
report.trade_setup = None
|
||
else:
|
||
report.trade_setup = self._generate_trade_setup(report, pip_value)
|
||
|
||
# ── 8. Reasons ─────────────────────────────────────────────
|
||
self._collect_reasons(report)
|
||
|
||
return report
|
||
|
||
# ── Internals ──────────────────────────────────────────────────
|
||
|
||
def _forex_sell_qualifies(self, report: SignalReport) -> bool:
|
||
"""Always returns False — forex SELL is structurally unprofitable.
|
||
0/4 trades won even under best conditions (trending_down + MTF + ADX>=25 + RSI<=50)."""
|
||
return False
|
||
|
||
def _check_xau_oversold_bounce(
|
||
self, report: SignalReport, dfs: Dict[Timeframe, pd.DataFrame]
|
||
) -> bool:
|
||
"""Return True when XAU/USD oversold-bounce conditions are met.
|
||
|
||
Conditions:
|
||
1. M15 RSI(14) < rsi_entry_threshold
|
||
2. Price > EMA(200) on at least min_ema200_tfs of {M15, H1, H4}
|
||
3. Current bar hour not in blocked list
|
||
"""
|
||
cfg = self.config.xau_strategy
|
||
|
||
try:
|
||
bar_hour = pd.Timestamp(report.timestamp).hour
|
||
if bar_hour in cfg.blocked_hours_utc:
|
||
return False
|
||
except Exception:
|
||
return False
|
||
|
||
m15_analysis = None
|
||
h4_analysis = None
|
||
for ca in report.confirmation_analyses:
|
||
if ca.timeframe == Timeframe.M15.value:
|
||
m15_analysis = ca
|
||
elif ca.timeframe == Timeframe.H4.value:
|
||
h4_analysis = ca
|
||
|
||
h1_analysis = report.primary_analysis
|
||
|
||
if not m15_analysis or not h1_analysis:
|
||
return False
|
||
|
||
m15_rsi = m15_analysis.indicators.get("rsi")
|
||
if not m15_rsi or m15_rsi.value >= cfg.rsi_entry_threshold:
|
||
return False
|
||
|
||
ema200_count = 0
|
||
|
||
m15_ema200 = m15_analysis.key_levels.get("ema_trend")
|
||
m15_df = dfs.get(Timeframe.M15)
|
||
if m15_df is not None and m15_ema200 is not None:
|
||
m15_price = float(m15_df["Close"].iloc[-1])
|
||
if m15_price > m15_ema200:
|
||
ema200_count += 1
|
||
|
||
h1_ema200 = h1_analysis.key_levels.get("ema_trend")
|
||
if h1_ema200 is not None and report.current_price > h1_ema200:
|
||
ema200_count += 1
|
||
|
||
if h4_analysis:
|
||
h4_ema200 = h4_analysis.key_levels.get("ema_trend")
|
||
h4_df = dfs.get(Timeframe.H4)
|
||
if h4_df is not None and h4_ema200 is not None:
|
||
h4_price = float(h4_df["Close"].iloc[-1])
|
||
if h4_price > h4_ema200:
|
||
ema200_count += 1
|
||
|
||
if ema200_count < cfg.min_ema200_tfs:
|
||
return False
|
||
|
||
return True
|
||
|
||
def _generate_xau_trade_setup(
|
||
self, report: SignalReport, dfs: Dict[Timeframe, pd.DataFrame]
|
||
) -> Optional[TradeSetup]:
|
||
"""Generate XAU-specific trade setup with backtested TP/SL."""
|
||
cfg = self.config.xau_strategy
|
||
|
||
m15_analysis = None
|
||
for ca in report.confirmation_analyses:
|
||
if ca.timeframe == Timeframe.M15.value:
|
||
m15_analysis = ca
|
||
break
|
||
|
||
if not m15_analysis:
|
||
return None
|
||
|
||
atr = m15_analysis.key_levels.get("atr", 0)
|
||
if atr <= 0:
|
||
return None
|
||
|
||
price = report.current_price
|
||
pip_value = 0.10
|
||
|
||
tp1 = price + cfg.tp_atr_multiplier * atr
|
||
sl = price - cfg.sl_atr_multiplier * atr
|
||
tp2 = price + cfg.tp_atr_multiplier * 2.0 * atr
|
||
|
||
sl_distance = price - sl
|
||
tp_distance = tp1 - price
|
||
rr = tp_distance / sl_distance if sl_distance > 0 else 0
|
||
|
||
return TradeSetup(
|
||
pair=report.symbol,
|
||
display_name=report.display_name,
|
||
direction="BUY",
|
||
entry_price=price,
|
||
stop_loss=round(sl, 2),
|
||
take_profit_1=round(tp1, 2),
|
||
take_profit_2=round(tp2, 2),
|
||
risk_reward=round(rr, 2),
|
||
risk_pips=round(sl_distance / pip_value, 1),
|
||
reward_pips=round(tp_distance / pip_value, 1),
|
||
pip_value=pip_value,
|
||
)
|
||
|
||
def _generate_xau_atr_trade_setup(
|
||
self, report: SignalReport, atr: float
|
||
) -> Optional[TradeSetup]:
|
||
"""XAU-aware exits for generic signals: wide SL, tight TP via ATR."""
|
||
cfg = self.config.xau_strategy
|
||
price = report.current_price
|
||
pip_value = 0.10
|
||
|
||
if report.final_signal in (SignalStrength.BUY, SignalStrength.STRONG_BUY):
|
||
is_buy = True
|
||
elif report.final_signal in (SignalStrength.SELL, SignalStrength.STRONG_SELL):
|
||
is_buy = False
|
||
else:
|
||
is_buy = report.final_score >= 0
|
||
|
||
if is_buy:
|
||
sl = price - cfg.sl_atr_multiplier * atr
|
||
tp1 = price + cfg.tp_atr_multiplier * atr
|
||
tp2 = price + cfg.tp_atr_multiplier * 2.0 * atr
|
||
direction = "BUY"
|
||
else:
|
||
sl = price + cfg.sl_atr_multiplier * atr
|
||
tp1 = price - cfg.tp_atr_multiplier * atr
|
||
tp2 = price - cfg.tp_atr_multiplier * 2.0 * atr
|
||
direction = "SELL"
|
||
|
||
sl_distance = abs(price - sl)
|
||
tp_distance = abs(tp1 - price)
|
||
rr = tp_distance / sl_distance if sl_distance > 0 else 0
|
||
|
||
return TradeSetup(
|
||
pair=report.symbol,
|
||
display_name=report.display_name,
|
||
direction=direction,
|
||
entry_price=price,
|
||
stop_loss=round(sl, 2),
|
||
take_profit_1=round(tp1, 2),
|
||
take_profit_2=round(tp2, 2),
|
||
risk_reward=round(rr, 2),
|
||
risk_pips=round(sl_distance / pip_value, 1),
|
||
reward_pips=round(tp_distance / pip_value, 1),
|
||
pip_value=pip_value,
|
||
)
|
||
|
||
def _check_eur_pullback_buy(
|
||
self, report: SignalReport, dfs: Dict[Timeframe, pd.DataFrame]
|
||
) -> bool:
|
||
"""Return True when EUR/USD pullback-buy conditions are met.
|
||
|
||
Conditions (all must be true):
|
||
0. Bar's weekday is in the universal allowed_weekdays list
|
||
1. Current bar hour not in blocked list
|
||
2. M15 RSI(14) in 30–55 (pullback, not overbought)
|
||
3. M15 BB position < 0.75 (not at resistance)
|
||
4. M15 price > EMA200 (uptrend)
|
||
5. H1 price > EMA200 (higher-TF confirmation)
|
||
6. Price within 1.5×ATR of EMA21 (not chasing)
|
||
"""
|
||
cfg = self.config.eur_strategy
|
||
|
||
try:
|
||
bar_ts = pd.Timestamp(report.timestamp)
|
||
bar_hour = bar_ts.hour
|
||
bar_wd = bar_ts.weekday()
|
||
if bar_hour in cfg.blocked_hours_utc:
|
||
return False
|
||
# Universal day filter — must be respected here because the
|
||
# strategy hook overwrites the section-6b filter's quality reset.
|
||
allowed_wd = self.config.backtest.allowed_weekdays
|
||
if allowed_wd and bar_wd not in allowed_wd:
|
||
return False
|
||
except Exception:
|
||
return False
|
||
|
||
m15_analysis = None
|
||
h1_analysis = None
|
||
|
||
if report.primary_analysis:
|
||
tf = report.primary_analysis.timeframe
|
||
if tf == Timeframe.M15.value:
|
||
m15_analysis = report.primary_analysis
|
||
elif tf == Timeframe.H1.value:
|
||
h1_analysis = report.primary_analysis
|
||
|
||
for ca in report.confirmation_analyses:
|
||
if ca.timeframe == Timeframe.M15.value:
|
||
m15_analysis = ca
|
||
elif ca.timeframe == Timeframe.H1.value:
|
||
h1_analysis = ca
|
||
|
||
if not m15_analysis or not h1_analysis:
|
||
return False
|
||
|
||
m15_rsi = m15_analysis.indicators.get("rsi")
|
||
if not m15_rsi or m15_rsi.value < cfg.rsi_lower or m15_rsi.value > cfg.rsi_upper:
|
||
return False
|
||
|
||
m15_bb = m15_analysis.indicators.get("bollinger")
|
||
if m15_bb and m15_bb.value > cfg.bb_max_position:
|
||
return False
|
||
|
||
m15_ema200 = m15_analysis.key_levels.get("ema_trend")
|
||
m15_df = dfs.get(Timeframe.M15)
|
||
if m15_df is None or m15_ema200 is None:
|
||
return False
|
||
m15_price = float(m15_df["Close"].iloc[-1])
|
||
if m15_price <= m15_ema200:
|
||
return False
|
||
|
||
h1_ema200 = h1_analysis.key_levels.get("ema_trend")
|
||
h1_df = dfs.get(Timeframe.H1)
|
||
if h1_ema200 is None:
|
||
return False
|
||
h1_price = float(h1_df["Close"].iloc[-1]) if h1_df is not None else report.current_price
|
||
if h1_price <= h1_ema200:
|
||
return False
|
||
|
||
m15_atr = m15_analysis.key_levels.get("atr", 0)
|
||
m15_ema21 = m15_analysis.key_levels.get("ema_medium")
|
||
if m15_atr > 0 and m15_ema21:
|
||
dist = abs(m15_price - m15_ema21) / m15_atr
|
||
if dist > cfg.chase_max_atr_from_ema21:
|
||
return False
|
||
|
||
# Minimum indicator confluence — rejects gate-passes with weak
|
||
# technical agreement. The pullback gate alone fires Quality=A
|
||
# even when M15 indicators are mostly neutral; this enforces
|
||
# actual confluence.
|
||
if cfg.min_indicators_agree > 0:
|
||
agreeing = sum(
|
||
1
|
||
for name in ("ema_trend", "rsi", "bollinger", "adx", "candlestick")
|
||
if (ind := m15_analysis.indicators.get(name)) is not None
|
||
and ind.signal in (SignalStrength.BUY, SignalStrength.STRONG_BUY)
|
||
)
|
||
if agreeing < cfg.min_indicators_agree:
|
||
return False
|
||
|
||
return True
|
||
|
||
def _generate_eur_trade_setup(
|
||
self, report: SignalReport, dfs: Dict[Timeframe, pd.DataFrame]
|
||
) -> Optional[TradeSetup]:
|
||
"""Generate EUR/USD-specific trade setup with tight TP / wide SL."""
|
||
cfg = self.config.eur_strategy
|
||
|
||
m15_analysis = None
|
||
if report.primary_analysis and report.primary_analysis.timeframe == Timeframe.M15.value:
|
||
m15_analysis = report.primary_analysis
|
||
else:
|
||
for ca in report.confirmation_analyses:
|
||
if ca.timeframe == Timeframe.M15.value:
|
||
m15_analysis = ca
|
||
break
|
||
|
||
if not m15_analysis:
|
||
return None
|
||
|
||
atr = m15_analysis.key_levels.get("atr", 0)
|
||
if atr <= 0:
|
||
return None
|
||
|
||
price = report.current_price
|
||
pip_value = 0.0001
|
||
|
||
tp1 = price + cfg.tp_atr_multiplier * atr
|
||
sl = price - cfg.sl_atr_multiplier * atr
|
||
tp2 = price + cfg.tp_atr_multiplier * 2.0 * atr
|
||
|
||
sl_distance = price - sl
|
||
tp_distance = tp1 - price
|
||
rr = tp_distance / sl_distance if sl_distance > 0 else 0
|
||
|
||
return TradeSetup(
|
||
pair=report.symbol,
|
||
display_name=report.display_name,
|
||
direction="BUY",
|
||
entry_price=price,
|
||
stop_loss=round(sl, 5),
|
||
take_profit_1=round(tp1, 5),
|
||
take_profit_2=round(tp2 , 5),
|
||
risk_reward=round(rr, 2),
|
||
risk_pips=round(sl_distance / pip_value, 1),
|
||
reward_pips=round(tp_distance / pip_value, 1),
|
||
pip_value=pip_value,
|
||
)
|
||
|
||
def _check_gbp_pullback_buy(
|
||
self, report: SignalReport, dfs: Dict[Timeframe, pd.DataFrame]
|
||
) -> bool:
|
||
"""GBP/USD pullback-buy — same logic as EUR, different config."""
|
||
cfg = self.config.gbp_strategy
|
||
|
||
try:
|
||
bar_ts = pd.Timestamp(report.timestamp)
|
||
bar_hour = bar_ts.hour
|
||
bar_wd = bar_ts.weekday()
|
||
if bar_hour in cfg.blocked_hours_utc:
|
||
return False
|
||
allowed_wd = self.config.backtest.allowed_weekdays
|
||
if allowed_wd and bar_wd not in allowed_wd:
|
||
return False
|
||
except Exception:
|
||
return False
|
||
|
||
m15_analysis = None
|
||
h1_analysis = None
|
||
|
||
if report.primary_analysis:
|
||
tf = report.primary_analysis.timeframe
|
||
if tf == Timeframe.M15.value:
|
||
m15_analysis = report.primary_analysis
|
||
elif tf == Timeframe.H1.value:
|
||
h1_analysis = report.primary_analysis
|
||
|
||
for ca in report.confirmation_analyses:
|
||
if ca.timeframe == Timeframe.M15.value:
|
||
m15_analysis = ca
|
||
elif ca.timeframe == Timeframe.H1.value:
|
||
h1_analysis = ca
|
||
|
||
if not m15_analysis or not h1_analysis:
|
||
return False
|
||
|
||
m15_rsi = m15_analysis.indicators.get("rsi")
|
||
if not m15_rsi or m15_rsi.value < cfg.rsi_lower or m15_rsi.value > cfg.rsi_upper:
|
||
return False
|
||
|
||
m15_bb = m15_analysis.indicators.get("bollinger")
|
||
if m15_bb and (m15_bb.value < cfg.bb_min_position or m15_bb.value > cfg.bb_max_position):
|
||
return False
|
||
|
||
m15_ema200 = m15_analysis.key_levels.get("ema_trend")
|
||
m15_df = dfs.get(Timeframe.M15)
|
||
if m15_df is None or m15_ema200 is None:
|
||
return False
|
||
m15_price = float(m15_df["Close"].iloc[-1])
|
||
if m15_price <= m15_ema200:
|
||
return False
|
||
|
||
h1_ema200 = h1_analysis.key_levels.get("ema_trend")
|
||
h1_df = dfs.get(Timeframe.H1)
|
||
if h1_ema200 is None:
|
||
return False
|
||
h1_price = float(h1_df["Close"].iloc[-1]) if h1_df is not None else report.current_price
|
||
if h1_price <= h1_ema200:
|
||
return False
|
||
|
||
m15_atr = m15_analysis.key_levels.get("atr", 0)
|
||
m15_ema21 = m15_analysis.key_levels.get("ema_medium")
|
||
if m15_atr > 0 and m15_ema21:
|
||
dist = abs(m15_price - m15_ema21) / m15_atr
|
||
if dist > cfg.chase_max_atr_from_ema21:
|
||
return False
|
||
|
||
# See EUR equivalent — enforce minimum indicator confluence.
|
||
if cfg.min_indicators_agree > 0:
|
||
agreeing = sum(
|
||
1
|
||
for name in ("ema_trend", "rsi", "bollinger", "adx", "candlestick")
|
||
if (ind := m15_analysis.indicators.get(name)) is not None
|
||
and ind.signal in (SignalStrength.BUY, SignalStrength.STRONG_BUY)
|
||
)
|
||
if agreeing < cfg.min_indicators_agree:
|
||
return False
|
||
|
||
return True
|
||
|
||
def _generate_gbp_trade_setup(
|
||
self, report: SignalReport, dfs: Dict[Timeframe, pd.DataFrame]
|
||
) -> Optional[TradeSetup]:
|
||
"""Generate GBP/USD trade setup with tight TP / balanced SL."""
|
||
cfg = self.config.gbp_strategy
|
||
|
||
m15_analysis = None
|
||
if report.primary_analysis and report.primary_analysis.timeframe == Timeframe.M15.value:
|
||
m15_analysis = report.primary_analysis
|
||
else:
|
||
for ca in report.confirmation_analyses:
|
||
if ca.timeframe == Timeframe.M15.value:
|
||
m15_analysis = ca
|
||
break
|
||
|
||
if not m15_analysis:
|
||
return None
|
||
|
||
atr = m15_analysis.key_levels.get("atr", 0)
|
||
if atr <= 0:
|
||
return None
|
||
|
||
price = report.current_price
|
||
pip_value = 0.0001
|
||
|
||
tp1 = price + cfg.tp_atr_multiplier * atr
|
||
sl = price - cfg.sl_atr_multiplier * atr
|
||
tp2 = price + cfg.tp_atr_multiplier * 2.0 * atr
|
||
|
||
sl_distance = price - sl
|
||
tp_distance = tp1 - price
|
||
rr = tp_distance / sl_distance if sl_distance > 0 else 0
|
||
|
||
return TradeSetup(
|
||
pair=report.symbol,
|
||
display_name=report.display_name,
|
||
direction="BUY",
|
||
entry_price=price,
|
||
stop_loss=round(sl, 5),
|
||
take_profit_1=round(tp1, 5),
|
||
take_profit_2=round(tp2, 5),
|
||
risk_reward=round(rr, 2),
|
||
risk_pips=round(sl_distance / pip_value, 1),
|
||
reward_pips=round(tp_distance / pip_value, 1),
|
||
pip_value=pip_value,
|
||
)
|
||
|
||
def _check_mtf_agreement(self, report: SignalReport) -> bool:
|
||
signals = list(report.mtf_signals.values())
|
||
if len(signals) < 2:
|
||
return False
|
||
|
||
bullish = sum(1 for s in signals if s in (SignalStrength.BUY, SignalStrength.STRONG_BUY))
|
||
bearish = sum(1 for s in signals if s in (SignalStrength.SELL, SignalStrength.STRONG_SELL))
|
||
|
||
threshold = self.config.signals.mtf_agreement_threshold
|
||
return bullish >= threshold or bearish >= threshold
|
||
|
||
def _compute_final_signal(self, report: SignalReport):
|
||
score = report.primary_score
|
||
confidence = report.primary_confidence
|
||
|
||
if report.mtf_agreement:
|
||
confidence += 10
|
||
all_scores = list(report.mtf_scores.values())
|
||
if all_scores:
|
||
mtf_avg = sum(all_scores) / len(all_scores)
|
||
score = score * 0.6 + mtf_avg * 0.4
|
||
else:
|
||
confidence -= 15
|
||
if len(report.mtf_scores) >= 2:
|
||
scores = list(report.mtf_scores.values())
|
||
has_bull = any(s > 10 for s in scores)
|
||
has_bear = any(s < -10 for s in scores)
|
||
if has_bull and has_bear:
|
||
report.warnings.append("Timeframes CONFLICT — mixed signals across timeframes")
|
||
|
||
if abs(report.news_sentiment) > 0.2:
|
||
if (report.news_sentiment > 0 and score > 0) or \
|
||
(report.news_sentiment < 0 and score < 0):
|
||
confidence += 5
|
||
elif (report.news_sentiment > 0 and score < -10) or \
|
||
(report.news_sentiment < 0 and score > 10):
|
||
report.warnings.append("News sentiment CONFLICTS with technical signal")
|
||
confidence -= 10
|
||
|
||
if report.event_risk == "danger":
|
||
report.warnings.append(f"EVENT RISK: {report.event_description}")
|
||
confidence = min(confidence, 30)
|
||
report.action_recommendation = f"WAIT — {report.event_description}"
|
||
elif report.event_risk == "caution":
|
||
report.warnings.append(f"Upcoming event: {report.event_description}")
|
||
confidence -= 15
|
||
|
||
is_counter_trend = (
|
||
(report.market_regime == "trending_up" and score < 0) or
|
||
(report.market_regime == "trending_down" and score > 0)
|
||
)
|
||
if is_counter_trend:
|
||
confidence -= 15
|
||
report.warnings.append("Counter-trend signal — reduced confidence")
|
||
|
||
if report.volatility_regime == "extreme":
|
||
report.warnings.append("EXTREME volatility — wider stops needed, reduced position size")
|
||
confidence -= 10
|
||
elif report.volatility_regime == "low":
|
||
report.warnings.append("Low volatility — potential for breakout, tight ranges")
|
||
|
||
is_xau = report.display_name == "XAU/USD"
|
||
|
||
primary = report.primary_analysis
|
||
if primary is not None:
|
||
ema200 = primary.key_levels.get("ema_trend")
|
||
if ema200 and ema200 > 0 and report.current_price > 0:
|
||
ema_dist_pct = abs(report.current_price - ema200) / ema200 * 100.0
|
||
_lo = float(os.environ.get("FB2_EMA_LO", "0.5"))
|
||
_hi = float(os.environ.get("FB2_EMA_HI", "1.5"))
|
||
if ema_dist_pct < _lo:
|
||
report.warnings.append(
|
||
f"NEAR EMA200 ({ema_dist_pct:.2f}%) — chop risk"
|
||
)
|
||
confidence -= 3 if is_xau else 10
|
||
elif ema_dist_pct > (2.5 if is_xau else _hi):
|
||
report.warnings.append(
|
||
f"FAR FROM EMA200 ({ema_dist_pct:.2f}%) — over-extended"
|
||
)
|
||
confidence -= 5 if is_xau else 10
|
||
|
||
atr = primary.key_levels.get("atr", 0)
|
||
if atr > 0 and score != 0:
|
||
is_buy_signal = score > 0
|
||
if is_buy_signal:
|
||
swing_lows = sorted(
|
||
v for k, v in primary.key_levels.items()
|
||
if k.startswith("swing_low_")
|
||
)
|
||
_exh_mult = 3.5 if is_xau else 2.5
|
||
if swing_lows and report.current_price - swing_lows[0] > _exh_mult * atr:
|
||
confidence -= 5 if is_xau else 15
|
||
report.warnings.append(f"TREND EXHAUSTION — price extended >{_exh_mult} ATR past swing low")
|
||
else:
|
||
swing_highs = sorted(
|
||
(v for k, v in primary.key_levels.items()
|
||
if k.startswith("swing_high_")),
|
||
reverse=True,
|
||
)
|
||
_exh_mult_s = 3.5 if is_xau else 2.5
|
||
if swing_highs and swing_highs[0] - report.current_price > _exh_mult_s * atr:
|
||
confidence -= 5 if is_xau else 15
|
||
report.warnings.append(f"TREND EXHAUSTION — price extended >{_exh_mult_s} ATR past swing high")
|
||
|
||
ema_medium = primary.key_levels.get("ema_medium")
|
||
if atr > 0 and ema_medium and report.market_regime.startswith("trending"):
|
||
pullback_dist = abs(report.current_price - ema_medium) / atr
|
||
_pb_severe = 2.5 if is_xau else 2.0
|
||
_pb_mild = 2.0 if is_xau else 1.5
|
||
if pullback_dist > _pb_severe:
|
||
confidence -= 8 if is_xau else 20
|
||
report.warnings.append(
|
||
f"NO PULLBACK — price {pullback_dist:.1f} ATR from EMA21, chasing risk"
|
||
)
|
||
elif pullback_dist > _pb_mild:
|
||
confidence -= 5 if is_xau else 10
|
||
report.warnings.append(
|
||
f"Weak pullback — price {pullback_dist:.1f} ATR from EMA21"
|
||
)
|
||
|
||
if report.market_regime.startswith("trending"):
|
||
rsi_ind = primary.indicators.get("rsi")
|
||
bb_ind = primary.indicators.get("bollinger")
|
||
|
||
if rsi_ind:
|
||
rsi_val = rsi_ind.value
|
||
_rsi_pen = 5 if is_xau else 15
|
||
if report.market_regime in ("trending_up", "trending") and score > 0:
|
||
if rsi_val > 65:
|
||
confidence -= _rsi_pen
|
||
report.warnings.append(
|
||
f"Extended entry — RSI {rsi_val:.0f} in uptrend (prefer pullback to 40-55)"
|
||
)
|
||
elif 38 <= rsi_val <= 55:
|
||
confidence += 5
|
||
elif report.market_regime == "trending_down" and score < 0:
|
||
if rsi_val < 35:
|
||
confidence -= _rsi_pen
|
||
report.warnings.append(
|
||
f"Extended entry — RSI {rsi_val:.0f} in downtrend (prefer bounce to 45-62)"
|
||
)
|
||
elif 45 <= rsi_val <= 62:
|
||
confidence += 5
|
||
|
||
if bb_ind:
|
||
bb_pos = bb_ind.value
|
||
if report.market_regime in ("trending_up", "trending") and score > 0:
|
||
if bb_pos > 0.85:
|
||
confidence -= 10
|
||
elif bb_pos < 0.4:
|
||
confidence += 5
|
||
elif report.market_regime == "trending_down" and score < 0:
|
||
if bb_pos < 0.15:
|
||
confidence -= 10
|
||
elif bb_pos > 0.6:
|
||
confidence += 5
|
||
|
||
confidence = max(0.0, min(95.0, confidence))
|
||
|
||
# Final signal
|
||
if not is_xau and score > 42:
|
||
confidence -= 10
|
||
report.warnings.append("EXHAUSTION: score > 42 — trend overextended")
|
||
if score >= 35 and confidence >= 55:
|
||
report.final_signal = SignalStrength.STRONG_BUY
|
||
elif score >= 25 and confidence >= 50:
|
||
report.final_signal = SignalStrength.BUY
|
||
elif score <= -35 and confidence >= 55:
|
||
report.final_signal = SignalStrength.STRONG_SELL
|
||
elif score <= -25 and confidence >= 50:
|
||
report.final_signal = SignalStrength.SELL
|
||
else:
|
||
report.final_signal = SignalStrength.NEUTRAL
|
||
|
||
report.final_score = score
|
||
report.final_confidence = confidence
|
||
|
||
# SELL suppression (pair-aware)
|
||
sell_suppressed = False
|
||
if self.config.backtest.sell_filter and report.final_signal in (
|
||
SignalStrength.SELL, SignalStrength.STRONG_SELL
|
||
):
|
||
if report.display_name not in self.config.backtest.sell_allowed_pairs:
|
||
report.final_signal = SignalStrength.NEUTRAL
|
||
report.warnings.append(f"SELL SUPPRESSED for {report.display_name}")
|
||
sell_suppressed = True
|
||
|
||
# Quality grade
|
||
abs_score = abs(score)
|
||
if sell_suppressed:
|
||
report.signal_quality = "F"
|
||
elif abs_score >= 40 and confidence >= 65 and report.mtf_agreement:
|
||
report.signal_quality = "A+"
|
||
elif abs_score >= 33 and confidence >= 55 and report.mtf_agreement:
|
||
report.signal_quality = "A"
|
||
elif abs_score >= 28 and confidence >= 50:
|
||
report.signal_quality = "B"
|
||
elif abs_score >= 25 and confidence >= 45:
|
||
report.signal_quality = "C"
|
||
elif abs_score >= 15:
|
||
report.signal_quality = "D"
|
||
else:
|
||
report.signal_quality = "F"
|
||
|
||
if not report.action_recommendation:
|
||
sig_name = report.final_signal.name.replace("_", " ")
|
||
if report.signal_quality in ("A+", "A"):
|
||
report.action_recommendation = f"{sig_name} — High-quality setup, consider entry"
|
||
elif report.signal_quality == "B":
|
||
report.action_recommendation = f"{sig_name} — Decent setup, wait for confirmation"
|
||
elif report.signal_quality in ("C", "D"):
|
||
report.action_recommendation = "WATCH — Signal present but low confidence"
|
||
else:
|
||
report.action_recommendation = "NO TRADE — No clear signal"
|
||
|
||
def _generate_trade_setup(self, report: SignalReport, pip_value: float) -> Optional[TradeSetup]:
|
||
if not report.primary_analysis:
|
||
return None
|
||
|
||
price = report.current_price
|
||
atr = report.primary_analysis.key_levels.get("atr", 0)
|
||
if atr == 0:
|
||
return None
|
||
|
||
# Fix 2: Minimum ATR threshold for XAU/USD
|
||
if report.display_name == "XAU/USD" and atr < self.config.xau_strategy.min_atr_threshold:
|
||
report.warnings.append(
|
||
f"LOW ATR FILTER: ATR ${atr:.2f} < ${self.config.xau_strategy.min_atr_threshold:.2f} minimum"
|
||
)
|
||
return None
|
||
|
||
min_sl_pips = 8.0 if pip_value < 0.01 else 80.0
|
||
min_sl_price = min_sl_pips * pip_value
|
||
|
||
if report.final_signal in (SignalStrength.BUY, SignalStrength.STRONG_BUY):
|
||
is_buy = True
|
||
elif report.final_signal in (SignalStrength.SELL, SignalStrength.STRONG_SELL):
|
||
is_buy = False
|
||
else:
|
||
is_buy = report.final_score >= 0
|
||
levels = report.primary_analysis.key_levels
|
||
min_rr = self.config.signals.min_rr_ratio
|
||
|
||
mature_move = abs(report.final_score) > 30
|
||
tp_mult = 0.9 if mature_move else 1.2
|
||
tp_swing_cap = 1.5 if mature_move else 2.0
|
||
|
||
# Fix 3: Wider SL multiplier for XAU/USD (1.8x vs default 1.5x)
|
||
sl_atr_floor = (self.config.xau_strategy.v2_sl_atr_multiplier
|
||
if report.display_name == "XAU/USD" else 1.5)
|
||
|
||
if is_buy:
|
||
swing_lows = sorted(
|
||
[v for k, v in levels.items() if k.startswith("swing_low_") and v < price],
|
||
reverse=True,
|
||
)
|
||
if swing_lows:
|
||
sl_price = swing_lows[0] - atr * 1.0
|
||
else:
|
||
sl_price = price - atr * 2.0
|
||
min_sl = max(atr * sl_atr_floor, min_sl_price)
|
||
if price - sl_price < min_sl:
|
||
sl_price = price - min_sl
|
||
|
||
sl_distance = price - sl_price
|
||
|
||
swing_highs = sorted(
|
||
v for k, v in levels.items() if k.startswith("swing_high_") and v > price + atr * 0.3
|
||
)
|
||
if (swing_highs
|
||
and swing_highs[0] - price <= atr * tp_swing_cap
|
||
and swing_highs[0] - price >= sl_distance * min_rr):
|
||
tp1 = swing_highs[0]
|
||
else:
|
||
tp1 = price + max(atr * tp_mult, sl_distance * min_rr)
|
||
if len(swing_highs) >= 2 and swing_highs[1] - price <= atr * 5.0:
|
||
tp2 = swing_highs[1]
|
||
else:
|
||
tp2 = price + max(atr * (tp_mult + 1.5), sl_distance * min_rr * 1.5)
|
||
|
||
direction = "BUY"
|
||
entry, sl = price, sl_price
|
||
else:
|
||
swing_highs = sorted(
|
||
v for k, v in levels.items() if k.startswith("swing_high_") and v > price
|
||
)
|
||
if swing_highs:
|
||
sl_price = swing_highs[0] + atr * 1.0
|
||
else:
|
||
sl_price = price + atr * 2.0
|
||
min_sl = max(atr * sl_atr_floor, min_sl_price)
|
||
if sl_price - price < min_sl:
|
||
sl_price = price + min_sl
|
||
|
||
sl_distance = sl_price - price
|
||
|
||
swing_lows = sorted(
|
||
[v for k, v in levels.items() if k.startswith("swing_low_") and v < price - atr * 0.3],
|
||
reverse=True,
|
||
)
|
||
if (swing_lows
|
||
and price - swing_lows[0] <= atr * tp_swing_cap
|
||
and price - swing_lows[0] >= sl_distance * min_rr):
|
||
tp1 = swing_lows[0]
|
||
else:
|
||
tp1 = price - max(atr * tp_mult, sl_distance * min_rr)
|
||
if len(swing_lows) >= 2 and price - swing_lows[1] <= atr * 5.0:
|
||
tp2 = swing_lows[1]
|
||
else:
|
||
tp2 = price - max(atr * (tp_mult + 1.5), sl_distance * min_rr * 1.5)
|
||
|
||
direction = "SELL"
|
||
entry, sl = price, sl_price
|
||
|
||
tp1_distance = abs(tp1 - entry)
|
||
rr = tp1_distance / sl_distance if sl_distance > 0 else 0
|
||
|
||
if rr < min_rr - 1e-9:
|
||
return None
|
||
|
||
risk_pips = sl_distance / pip_value
|
||
reward_pips = tp1_distance / pip_value
|
||
|
||
return TradeSetup(
|
||
pair=report.symbol,
|
||
display_name=report.display_name,
|
||
direction=direction,
|
||
entry_price=entry,
|
||
stop_loss=sl,
|
||
take_profit_1=tp1,
|
||
take_profit_2=tp2,
|
||
risk_reward=round(rr, 2),
|
||
risk_pips=risk_pips,
|
||
reward_pips=reward_pips,
|
||
pip_value=pip_value,
|
||
)
|
||
|
||
def _collect_reasons(self, report: SignalReport):
|
||
if not report.primary_analysis:
|
||
return
|
||
|
||
for name, ind in report.primary_analysis.indicators.items():
|
||
if name.startswith("_") or ind.weight == 0:
|
||
continue
|
||
if ind.signal in (SignalStrength.BUY, SignalStrength.STRONG_BUY):
|
||
prefix = "STRONG: " if ind.signal == SignalStrength.STRONG_BUY else ""
|
||
report.bullish_reasons.append(f"{prefix}{ind.name}: {ind.description}")
|
||
elif ind.signal in (SignalStrength.SELL, SignalStrength.STRONG_SELL):
|
||
prefix = "STRONG: " if ind.signal == SignalStrength.STRONG_SELL else ""
|
||
report.bearish_reasons.append(f"{prefix}{ind.name}: {ind.description}")
|
||
|
||
if report.news_sentiment > 0.1:
|
||
report.bullish_reasons.append(f"News: {report.news_description}")
|
||
elif report.news_sentiment < -0.1:
|
||
report.bearish_reasons.append(f"News: {report.news_description}")
|