Backtest tuning, data freshness guard, Telegram improvements
- Drop USD/JPY from scan pairs (zero signals across all timeframes) - Disable divergence indicator (zero impact in 14-config lab test) - Parallelize evaluate.py with ProcessPoolExecutor (16 cores) - Add --pair CLI filter to evaluate.py for single-pair backtests - Add data freshness guard: stale cache auto-invalidated, primary TF stale data suppresses signals to prevent trading on old data - Add /cache command: shows fetch age and last bar per pair/TF - Add /clearcache command: wipes in-memory cache for fresh API fetch - Remove BB from WebSocket breach alerts (keep structural levels only) - Show live prices only for WS-monitored pairs (EUR/USD, XAU/USD) - Replace arrow emojis with text tags in indicator lines
This commit is contained in:
harwinder
+156
-20
@@ -110,9 +110,13 @@ class SignalAggregator:
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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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dfs[tf] = self.data_provider.fetch_ohlcv(symbol, tf)
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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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@@ -123,6 +127,14 @@ class SignalAggregator:
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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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@@ -206,12 +218,12 @@ class SignalAggregator:
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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).mean()
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plus_di = 100 * (plus_dm.ewm(alpha=1/period, min_periods=period).mean() / atr_s)
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minus_di = 100 * (minus_dm.ewm(alpha=1/period, min_periods=period).mean() / atr_s)
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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).mean().dropna()
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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])
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@@ -308,9 +320,32 @@ class SignalAggregator:
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# ── 6. Final signal ────────────────────────────────────────
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self._compute_final_signal(report)
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# ── 6b. Session filter (works for both live and backtest) ─
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if self.config.backtest.session_filter:
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try:
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bar_hour = pd.Timestamp(report.timestamp).hour
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if bar_hour in self.config.backtest.blocked_hours_utc:
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report.final_signal = SignalStrength.NEUTRAL
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report.signal_quality = "F"
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report.warnings.append(f"SESSION FILTER: {bar_hour:02}:00 UTC blocked")
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except Exception:
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pass
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# ── 7. Trade setup for actionable signals ──────────────────
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if report.signal_quality in ("A+", "A", "B", "C"):
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report.trade_setup = self._generate_trade_setup(report, pip_value)
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is_sell_direction = (
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report.final_signal in (SignalStrength.SELL, SignalStrength.STRONG_SELL)
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or (report.final_signal == SignalStrength.NEUTRAL and report.final_score < 0)
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)
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if is_sell_direction and self.config.backtest.sell_filter:
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if report.display_name in self.config.backtest.sell_allowed_pairs:
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report.trade_setup = self._generate_trade_setup(report, pip_value)
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elif self._forex_sell_qualifies(report):
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report.trade_setup = self._generate_trade_setup(report, pip_value)
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else:
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report.trade_setup = None
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else:
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report.trade_setup = self._generate_trade_setup(report, pip_value)
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# ── 8. Reasons ─────────────────────────────────────────────
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self._collect_reasons(report)
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@@ -319,6 +354,11 @@ class SignalAggregator:
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# ── Internals ──────────────────────────────────────────────────
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def _forex_sell_qualifies(self, report: SignalReport) -> bool:
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"""Always returns False — forex SELL is structurally unprofitable.
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0/4 trades won even under best conditions (trending_down + MTF + ADX>=25 + RSI<=50)."""
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return False
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def _check_mtf_agreement(self, report: SignalReport) -> bool:
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signals = list(report.mtf_signals.values())
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if len(signals) < 2:
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@@ -398,16 +438,90 @@ class SignalAggregator:
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)
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confidence -= 10
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atr = primary.key_levels.get("atr", 0)
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if atr > 0 and score != 0:
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is_buy_signal = score > 0
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if is_buy_signal:
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swing_lows = sorted(
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v for k, v in primary.key_levels.items()
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if k.startswith("swing_low_")
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)
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if swing_lows and report.current_price - swing_lows[0] > 2.5 * atr:
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confidence -= 15
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report.warnings.append("TREND EXHAUSTION — price extended >2.5 ATR past swing low")
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else:
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swing_highs = sorted(
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(v for k, v in primary.key_levels.items()
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if k.startswith("swing_high_")),
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reverse=True,
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)
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if swing_highs and swing_highs[0] - report.current_price > 2.5 * atr:
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confidence -= 15
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report.warnings.append("TREND EXHAUSTION — price extended >2.5 ATR past swing high")
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ema_medium = primary.key_levels.get("ema_medium")
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if atr > 0 and ema_medium and report.market_regime.startswith("trending"):
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pullback_dist = abs(report.current_price - ema_medium) / atr
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if pullback_dist > 2.0:
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confidence -= 20
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report.warnings.append(
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f"NO PULLBACK — price {pullback_dist:.1f} ATR from EMA21, chasing risk"
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)
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elif pullback_dist > 1.5:
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confidence -= 10
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report.warnings.append(
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f"Weak pullback — price {pullback_dist:.1f} ATR from EMA21"
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)
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if report.market_regime.startswith("trending"):
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rsi_ind = primary.indicators.get("rsi")
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bb_ind = primary.indicators.get("bollinger")
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if rsi_ind:
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rsi_val = rsi_ind.value
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if report.market_regime in ("trending_up", "trending") and score > 0:
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if rsi_val > 65:
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confidence -= 15
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report.warnings.append(
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f"Extended entry — RSI {rsi_val:.0f} in uptrend (prefer pullback to 40-55)"
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)
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elif 38 <= rsi_val <= 55:
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confidence += 5
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elif report.market_regime == "trending_down" and score < 0:
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if rsi_val < 35:
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confidence -= 15
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report.warnings.append(
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f"Extended entry — RSI {rsi_val:.0f} in downtrend (prefer bounce to 45-62)"
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)
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elif 45 <= rsi_val <= 62:
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confidence += 5
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if bb_ind:
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bb_pos = bb_ind.value
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if report.market_regime in ("trending_up", "trending") and score > 0:
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if bb_pos > 0.85:
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confidence -= 10
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elif bb_pos < 0.4:
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confidence += 5
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elif report.market_regime == "trending_down" and score < 0:
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if bb_pos < 0.15:
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confidence -= 10
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elif bb_pos > 0.6:
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confidence += 5
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confidence = max(0.0, min(95.0, confidence))
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# Final signal
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if score >= 35 and confidence >= 60:
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if score > 38:
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confidence -= 20
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report.warnings.append("EXHAUSTION: score > 38 — trend overextended")
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if score >= 40 and confidence >= 60:
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report.final_signal = SignalStrength.STRONG_BUY
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elif score >= 12 and confidence >= 45:
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elif score >= 30 and confidence >= 55:
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report.final_signal = SignalStrength.BUY
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elif score <= -35 and confidence >= 60:
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elif score <= -40 and confidence >= 60:
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report.final_signal = SignalStrength.STRONG_SELL
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elif score <= -12 and confidence >= 45:
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elif score <= -30 and confidence >= 55:
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report.final_signal = SignalStrength.SELL
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else:
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report.final_signal = SignalStrength.NEUTRAL
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@@ -415,17 +529,29 @@ class SignalAggregator:
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report.final_score = score
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report.final_confidence = confidence
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# SELL suppression (pair-aware)
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sell_suppressed = False
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if self.config.backtest.sell_filter and report.final_signal in (
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SignalStrength.SELL, SignalStrength.STRONG_SELL
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):
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if report.display_name not in self.config.backtest.sell_allowed_pairs:
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report.final_signal = SignalStrength.NEUTRAL
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report.warnings.append(f"SELL SUPPRESSED for {report.display_name}")
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sell_suppressed = True
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# Quality grade
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abs_score = abs(score)
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if abs_score >= 45 and confidence >= 70 and report.mtf_agreement:
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if sell_suppressed:
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report.signal_quality = "F"
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elif abs_score >= 45 and confidence >= 70 and report.mtf_agreement:
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report.signal_quality = "A+"
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elif abs_score >= 30 and confidence >= 60 and report.mtf_agreement:
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elif abs_score >= 38 and confidence >= 60 and report.mtf_agreement:
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report.signal_quality = "A"
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elif abs_score >= 20 and confidence >= 50:
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elif abs_score >= 33 and confidence >= 55:
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report.signal_quality = "B"
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elif abs_score >= 12 and confidence >= 40:
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elif abs_score >= 30 and confidence >= 50:
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report.signal_quality = "C"
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elif abs_score >= 8:
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elif abs_score >= 15:
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report.signal_quality = "D"
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else:
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report.signal_quality = "F"
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@@ -450,7 +576,15 @@ class SignalAggregator:
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if atr == 0:
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return None
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is_buy = report.final_signal in (SignalStrength.BUY, SignalStrength.STRONG_BUY)
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min_sl_pips = 8.0 if pip_value < 0.01 else 80.0
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min_sl_price = min_sl_pips * pip_value
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if report.final_signal in (SignalStrength.BUY, SignalStrength.STRONG_BUY):
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is_buy = True
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elif report.final_signal in (SignalStrength.SELL, SignalStrength.STRONG_SELL):
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is_buy = False
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else:
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is_buy = report.final_score >= 0
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levels = report.primary_analysis.key_levels
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min_rr = self.config.signals.min_rr_ratio
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@@ -467,8 +601,9 @@ class SignalAggregator:
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sl_price = swing_lows[0] - atr * 1.0
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else:
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sl_price = price - atr * 2.0
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if price - sl_price < atr * 1.5:
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sl_price = price - atr * 1.5
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min_sl = max(atr * 1.5, min_sl_price)
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if price - sl_price < min_sl:
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sl_price = price - min_sl
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sl_distance = price - sl_price
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@@ -496,8 +631,9 @@ class SignalAggregator:
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sl_price = swing_highs[0] + atr * 1.0
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else:
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sl_price = price + atr * 2.0
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if sl_price - price < atr * 1.5:
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sl_price = price + atr * 1.5
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min_sl = max(atr * 1.5, min_sl_price)
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if sl_price - price < min_sl:
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sl_price = price + min_sl
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sl_distance = sl_price - price
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