layer one v5

config.py

@@ -212,16 +212,18 @@ CURRENCY_EMOJIS = {
 MT5_SYMBOL_SUFFIX = os.getenv("MT5_SYMBOL_SUFFIX", "")
 
 # Technical Analysis Settings
-Z_SCORE_THRESHOLD = float(os.getenv("Z_SCORE_THRESHOLD", 2.0))  # Overbought/oversold level
+Z_SCORE_THRESHOLD = float(os.getenv("Z_SCORE_THRESHOLD", 2.0))  # Overbought/oversold level (legacy/macro)
+SCALP_Z_SCORE_THRESHOLD = float(os.getenv("SCALP_Z_SCORE_THRESHOLD", 1.5))  # Intraday threshold (more sensitive)
+SCALP_MIN_GAP_TO_TRADE = float(os.getenv("SCALP_MIN_GAP", 2.0))  # Intraday min gap (sigma units)
 
-# Multi-timeframe configuration
+# Multi-timeframe configuration (short lookbacks for scalping)
 TIMEFRAMES = {
-    "M5":  {"interval": "5min",  "bars": 288, "label": "5 min"},
-    "M15": {"interval": "15min", "bars": 96,  "label": "15 min"},
-    "H1":  {"interval": "1h",    "bars": 48,  "label": "1 hour"},
-    "H4":  {"interval": "4h",    "bars": 24,  "label": "4 hour"},
+    "M5":  {"interval": "5min",  "bars": 48,  "label": "5 min"},
+    "M15": {"interval": "15min", "bars": 16,  "label": "15 min"},
+    "H1":  {"interval": "1h",    "bars": 12,  "label": "1 hour"},
+    "H4":  {"interval": "4h",    "bars": 6,   "label": "4 hour"},
 }
-DEFAULT_TIMEFRAME = os.getenv("DEFAULT_TIMEFRAME", "M15")
+DEFAULT_TIMEFRAME = os.getenv("DEFAULT_TIMEFRAME", "M5")
 
 # Historical bar config (backward compat)
 BAR_TIMEFRAME = os.getenv("BAR_TIMEFRAME", "M5")
@@ -241,7 +243,17 @@ SESSION_LONDON_CLOSE = 16 # 16:00 UTC
 SESSION_NEWYORK_OPEN = 13 # 13:00 UTC
 SESSION_NEWYORK_CLOSE = 21# 21:00 UTC
 
-# Confluence Settings
+# ============================================================================
+# Confluence Layer Weights (Scalper Profile)
+# ============================================================================
+# Effective weight distribution for signal display:
+#   - Market Structure + Order Flow (Currency Strength Matrix / Z-scores): ~65%
+#   - Currency Power Matrix (Session SRV + momentum): ~25%
+#   - Macro / Fundamental Backdrop (Layer 1 scorer, advisory only): ~10%
+#
+# The macro layer is DISPLAY ONLY — it never blocks or vetoes a trade signal.
+# Currency Power Matrix refers to CurrencyStrengthMatrix (this engine).
+# ============================================================================
 CONFLUENCE_ENABLED = os.getenv("CONFLUENCE_ENABLED", "true").lower() == "true"
 MIN_CONFLUENCE_STRENGTH = float(os.getenv("MIN_CONFLUENCE_STRENGTH", 60.0))  # 60% confidence threshold
 

confluence_filter.py

@@ -72,13 +72,10 @@ class ConfluenceFilter:
             print(f"[Confluence] Monthly bias matrix set: {directions}")
 
     def _check_boundary(self, short_ccy: str, long_ccy: str) -> Tuple[bool, str]:
-        """Check if a proposed trade crosses the Layer 1 macro boundary.
+        """Advisory-only macro boundary check — does NOT block any signal.
 
-        A trade proposes SHORT short_ccy + LONG long_ccy.
-        Boundary rules:
-          - STRONG currencies cannot be shorted
-          - WEAK currencies cannot be longed
-          - NEUTRAL currencies have no restriction
+        Returns (True, reason) always. The bias matrix is displayed for
+        context in the UI but never gates/ vetoes a trade signal.
 
         Returns:
             (allowed: bool, reason: str)
@@ -89,17 +86,13 @@ class ConfluenceFilter:
         short_dir = self.bias_matrix.get(short_ccy, {}).get("direction", "NEUTRAL")
         long_dir = self.bias_matrix.get(long_ccy, {}).get("direction", "NEUTRAL")
 
+        notes = []
         if short_dir == "STRONG":
-            return (
-                False,
-                f"Cannot short {short_ccy}: classified STRONG by Layer 1 macro bias"
-            )
+            notes.append(f"{short_ccy}=STRONG (advisory)")
         if long_dir == "WEAK":
-            return (
-                False,
-                f"Cannot long {long_ccy}: classified WEAK by Layer 1 macro bias"
-            )
-        return True, "Within macro boundary"
+            notes.append(f"{long_ccy}=WEAK (advisory)")
+        advisory = f"Within macro boundary — {' | '.join(notes) if notes else 'neutral'}"
+        return True, advisory
 
     def check_entry_confluence(self, current_prices: Dict[str, float] = None
                                ) -> Tuple[bool, str, float, Optional[Dict]]:
@@ -109,58 +102,45 @@ class ConfluenceFilter:
             mc = self.matrix.get_matrix_cross()
             gap = self.matrix.get_divergence_gap()
 
-            if mc and "_" in mc:
+            if mc and "_" in mc and gap >= config.SCALP_MIN_GAP_TO_TRADE:
                 short_ccy, long_ccy = mc.split("_", 1)
-                allowed, reason = self._check_boundary(short_ccy, long_ccy)
-                if allowed:
-                    confidence = min(abs(gap) / 4.0, 1.0) * 100
-                    self.confluence_strength = confidence
-                    self.last_confluence_check = datetime.now()
-                    direction = "SHORT" if confidence > 50 else "LONG"
-                    entry = self.tech_analyzer.get_last_price(mc) or 0.0
-                    sl_tp = self.tech_analyzer.calculate_sl_tp(mc, direction, entry)
-                    if self.db:
-                        self.db.save_confluence_signal(
-                            pair=mc, signal_type="MATRIX_DIVERGENCE",
-                            confidence=confidence, z_score=None, gap=gap,
-                            reason=f"Matrix cross {mc} gap={gap:.1f}σ",
-                            layer1_active=self.layer1_is_active,
-                        )
-                    return (True, f"MATRIX DIVERGENCE: {mc} (Gap: {gap:.1f}σ)", confidence, sl_tp)
-                else:
-                    self.confluence_strength = 0.0
-                    self.last_confluence_check = datetime.now()
-                    return (False, f"MATRIX DIVERGENCE BLOCKED — {reason}", 0.0, None)
+                _, advisory = self._check_boundary(short_ccy, long_ccy)
+                confidence = min(abs(gap) / 4.0, 1.0) * 100
+                self.confluence_strength = confidence
+                self.last_confluence_check = datetime.now()
+                direction = "SHORT" if confidence > 50 else "LONG"
+                entry = self.tech_analyzer.get_last_price(mc) or 0.0
+                sl_tp = self.tech_analyzer.calculate_sl_tp(mc, direction, entry)
+                if self.db:
+                    self.db.save_confluence_signal(
+                        pair=mc, signal_type="MATRIX_DIVERGENCE",
+                        confidence=confidence, z_score=None, gap=gap,
+                        reason=f"Matrix cross {mc} gap={gap:.1f}σ | {advisory}",
+                        layer1_active=self.layer1_is_active,
+                    )
+                return (True, f"MATRIX DIVERGENCE: {mc} (Gap: {gap:.1f}σ)", confidence, sl_tp)
 
         all_z = self.tech_analyzer.get_all_z_scores()
         sorted_pairs = sorted(all_z.items(), key=lambda x: abs(x[1]), reverse=True)
 
         for pair, z_score in sorted_pairs:
-            if abs(z_score) < config.Z_SCORE_THRESHOLD:
+            if abs(z_score) < config.SCALP_Z_SCORE_THRESHOLD:
                 continue
 
-            base, quote = pair.split("_")
-            if z_score > 0:
-                short_ccy, long_ccy = base, quote
-            else:
-                short_ccy, long_ccy = quote, base
-
-            allowed, reason = self._check_boundary(short_ccy, long_ccy)
-            if allowed:
-                confidence = min(abs(z_score) / 3.0, 1.0) * 100
-                self.confluence_strength = confidence
-                self.last_confluence_check = datetime.now()
-                direction = "SHORT" if z_score > 0 else "LONG"
-                entry = self.tech_analyzer.get_last_price(pair) or 0.0
-                sl_tp = self.tech_analyzer.calculate_sl_tp(pair, direction, entry)
-                if self.db:
-                    self.db.save_confluence_signal(
-                        pair=pair, signal_type="PAIR_EXTREME",
-                        confidence=confidence, z_score=z_score,
-                        reason=f"Z={z_score:.2f} within macro boundary",
-                        layer1_active=self.layer1_is_active,
-                    )
-                return (True, f"PAIR EXTREME: {pair} Z={z_score:.2f}", confidence, sl_tp)
+            confidence = min(abs(z_score) / 3.0, 1.0) * 100
+            self.confluence_strength = confidence
+            self.last_confluence_check = datetime.now()
+            direction = "SHORT" if z_score > 0 else "LONG"
+            entry = self.tech_analyzer.get_last_price(pair) or 0.0
+            sl_tp = self.tech_analyzer.calculate_sl_tp(pair, direction, entry)
+            if self.db:
+                self.db.save_confluence_signal(
+                    pair=pair, signal_type="PAIR_EXTREME",
+                    confidence=confidence, z_score=z_score,
+                    reason=f"Z={z_score:.2f}",
+                    layer1_active=self.layer1_is_active,
+                )
+            return (True, f"PAIR EXTREME: {pair} Z={z_score:.2f}", confidence, sl_tp)
 
         return (False, "No valid signals within macro boundary", 0.0, None)
 
@@ -181,23 +161,7 @@ class ConfluenceFilter:
         return False, "Position still valid"
 
     def is_conflicting(self) -> bool:
-        """Check if any extreme Layer 2 signal crosses the macro boundary."""
-        if not self.bias_matrix:
-            return False
-
-        all_z = self.tech_analyzer.get_all_z_scores()
-        for pair, z_score in all_z.items():
-            if abs(z_score) < config.Z_SCORE_THRESHOLD:
-                continue
-            base, quote = pair.split("_")
-            if z_score > 0:
-                short_dir = self.bias_matrix.get(base, {}).get("direction", "NEUTRAL")
-                long_dir = self.bias_matrix.get(quote, {}).get("direction", "NEUTRAL")
-            else:
-                short_dir = self.bias_matrix.get(quote, {}).get("direction", "NEUTRAL")
-                long_dir = self.bias_matrix.get(base, {}).get("direction", "NEUTRAL")
-            if short_dir == "STRONG" or long_dir == "WEAK":
-                return True
+        """Advisory-only check — always returns False (does not block signals)."""
         return False
 
     def get_confluence_report(self, current_prices: Dict[str, float] = None) -> Dict:
@@ -250,50 +214,39 @@ class ConfluenceFilter:
             if mc:
                 gap = self.matrix.get_divergence_gap()
                 strength = min(abs(gap) / 4.0, 1.0) * 100
-                short_ccy, long_ccy = mc.split("_", 1)
-                allowed, _ = self._check_boundary(short_ccy, long_ccy)
-                if allowed:
-                    direction = 'SHORT' if strength > 50 else 'LONG'
-                    entry = self.tech_analyzer.get_last_price(mc) or 0.0
-                    sl_tp = self.tech_analyzer.calculate_sl_tp(mc, "LONG" if direction == "LONG" else "SHORT", entry)
-                    signals[mc] = {
-                        'pair': mc,
-                        'type': 'MATRIX_DIVERGENCE',
-                        'strength': strength,
-                        'reason': f"Matrix cross {mc} (spread: {gap:.2f}σ)",
-                        'direction': direction,
-                        **sl_tp,
-                    }
+                direction = 'SHORT' if strength > 50 else 'LONG'
+                entry = self.tech_analyzer.get_last_price(mc) or 0.0
+                sl_tp = self.tech_analyzer.calculate_sl_tp(mc, "LONG" if direction == "LONG" else "SHORT", entry)
+                signals[mc] = {
+                    'pair': mc,
+                    'type': 'MATRIX_DIVERGENCE',
+                    'strength': strength,
+                    'reason': f"Matrix cross {mc} (spread: {gap:.2f}σ)",
+                    'direction': direction,
+                    **sl_tp,
+                }
 
         for pair, z_score in sorted(
             self.tech_analyzer.get_all_z_scores().items(),
             key=lambda x: abs(x[1]), reverse=True
         ):
-            if abs(z_score) < config.Z_SCORE_THRESHOLD:
+            if abs(z_score) < config.SCALP_Z_SCORE_THRESHOLD:
                 continue
             if pair in signals:
                 continue
 
-            base, quote = pair.split("_")
-            if z_score > 0:
-                short_ccy, long_ccy = base, quote
-            else:
-                short_ccy, long_ccy = quote, base
-
-            allowed, _ = self._check_boundary(short_ccy, long_ccy)
-            if allowed:
-                strength = min(abs(z_score) / 3.0, 1.0) * 100
-                direction = 'SHORT' if z_score > 0 else 'LONG'
-                entry = self.tech_analyzer.get_last_price(pair) or 0.0
-                sl_tp = self.tech_analyzer.calculate_sl_tp(pair, "LONG" if direction == "LONG" else "SHORT", entry)
-                signals[pair] = {
-                    'pair': pair,
-                    'type': 'PAIR_EXTREME',
-                    'strength': strength,
-                    'reason': f"{pair} Z={z_score:.2f} within macro boundary",
-                    'direction': direction,
-                    **sl_tp,
-                }
+            strength = min(abs(z_score) / 3.0, 1.0) * 100
+            direction = 'SHORT' if z_score > 0 else 'LONG'
+            entry = self.tech_analyzer.get_last_price(pair) or 0.0
+            sl_tp = self.tech_analyzer.calculate_sl_tp(pair, "LONG" if direction == "LONG" else "SHORT", entry)
+            signals[pair] = {
+                'pair': pair,
+                'type': 'PAIR_EXTREME',
+                'strength': strength,
+                'reason': f"{pair} Z={z_score:.2f}",
+                'direction': direction,
+                **sl_tp,
+            }
 
         return signals
 

currency_strength_matrix.py

@@ -80,7 +80,7 @@ class CurrencyStrengthMatrix:
 
     def __init__(self, z_scores: Dict[str, float] = None):
         self.currencies = config.CURRENCIES
-        self.threshold = config.Z_SCORE_THRESHOLD
+        self.threshold = config.SCALP_Z_SCORE_THRESHOLD
         self._raw_scores: Dict[str, List[float]] = {}
         self._strengths: Dict[str, CurrencyStrength] = {}
         self.session_tracker = SessionTracker()

layer2_technical.py

@@ -97,7 +97,7 @@ class TechnicalAnalyzer:
         current_price = prices[-1]
         z_score = (current_price - mu) / sigma
         self.z_scores[currency_pair] = z_score
-        self.extremes[currency_pair] = abs(z_score) >= config.Z_SCORE_THRESHOLD
+        self.extremes[currency_pair] = abs(z_score) >= config.SCALP_Z_SCORE_THRESHOLD
 
     def get_z_score(self, currency_pair: str) -> float:
         return self.z_scores.get(currency_pair, 0.0)
@@ -106,10 +106,10 @@ class TechnicalAnalyzer:
         return self.extremes.get(currency_pair, False)
 
     def get_overbought_pairs(self) -> List[str]:
-        return [pair for pair, z in self.z_scores.items() if z >= config.Z_SCORE_THRESHOLD]
+        return [pair for pair, z in self.z_scores.items() if z >= config.SCALP_Z_SCORE_THRESHOLD]
 
     def get_oversold_pairs(self) -> List[str]:
-        return [pair for pair, z in self.z_scores.items() if z <= -config.Z_SCORE_THRESHOLD]
+        return [pair for pair, z in self.z_scores.items() if z <= -config.SCALP_Z_SCORE_THRESHOLD]
 
     def get_volatility(self, currency_pair: str) -> float:
         bars = list(self.bar_history[currency_pair])
@@ -191,7 +191,7 @@ class TechnicalAnalyzer:
                 if ticks and sigma > 0:
                     z = (ticks[-1] - mu) / sigma
                     self.z_scores[pair] = z
-                    self.extremes[pair] = abs(z) >= config.Z_SCORE_THRESHOLD
+                    self.extremes[pair] = abs(z) >= config.SCALP_Z_SCORE_THRESHOLD
 
     def seed_ohlc(self, ohlc_data: Dict[str, List[Dict]]):
         """Seed both bar_history and ohlc_history from full candle data.
@@ -213,7 +213,7 @@ class TechnicalAnalyzer:
                 if ticks and sigma > 0:
                     z = (ticks[-1] - mu) / sigma
                     self.z_scores[pair] = z
-                    self.extremes[pair] = abs(z) >= config.Z_SCORE_THRESHOLD
+                    self.extremes[pair] = abs(z) >= config.SCALP_Z_SCORE_THRESHOLD
 
     def clear_history(self):
         for pair in self.bar_history:

main_window.py

@@ -20,11 +20,12 @@ Responsibilities:
 """
 
 from PyQt5.QtWidgets import QMainWindow, QTabWidget, QMessageBox
-from PyQt5.QtCore import QThread, pyqtSignal
+from PyQt5.QtCore import QThread, pyqtSignal, QTimer
 from typing import Dict, Optional
 import config
 from database import Database
 from layer2_technical import TechnicalAnalyzer
+from currency_strength_matrix import CurrencyStrengthMatrix
 from ui.dashboard_tab import DashboardTab
 from ui.entry_tab import MonthlyEntryTab
 from ui.layer2_monitor_tab import Layer2MonitorTab
@@ -115,6 +116,7 @@ class MainWindow(QMainWindow):
         self._init_ui()
         self._connect_signals()
         self._setup_auto_fetch()
+        self._setup_live_signal_timer()
     
     def _init_ui(self):
         """Build the main window UI."""
@@ -124,8 +126,8 @@ class MainWindow(QMainWindow):
         # Tab widget
         tabs = QTabWidget()
         
-        # Tab 1: Dashboard (Layer 1)
-        self.dashboard_tab = DashboardTab(self.db)
+        # Tab 1: Dashboard (Live + Macro Backdrop)
+        self.dashboard_tab = DashboardTab(self.db, tech_analyzer=self.tech_analyzer)
         tabs.addTab(self.dashboard_tab, config.TAB_NAMES["dashboard"])
         
         # Tab 2: Monthly Entry (Data input)
@@ -172,6 +174,17 @@ class MainWindow(QMainWindow):
                 print("[Main] Auto-fetch enabled, fetching rates on startup...")
             self._fetch_rates()
     
+    def _setup_live_signal_timer(self):
+        """Periodically refresh the live intraday signal on the dashboard."""
+        self._live_signal_timer = QTimer()
+        self._live_signal_timer.timeout.connect(self._tick_live_signal)
+        self._live_signal_timer.start(3000)
+
+    def _tick_live_signal(self):
+        """Refresh live signal on dashboard."""
+        if self.dashboard_tab:
+            self.dashboard_tab.update_live_signal()
+
     def _fetch_rates(self):
         """
         Trigger background FRED rate fetch.

scorer.py

@@ -253,17 +253,14 @@ def generate_signal(scores: Dict[str, Dict]) -> Tuple[str, str, str]:
 
 
 def build_directional_bias_matrix(scores: Dict[str, Dict]) -> Dict[str, Dict]:
-    """Build a permanent monthly directional bias matrix from Layer 1 scores.
+    """Build an advisory directional bias matrix from Layer 1 scores.
 
-    Rules:
-      - Top 2 scores → "STRONG" — currency must only be longed, never shorted
-      - Bottom 2 scores → "WEAK" — currency must only be shorted, never longed
-      - Middle 4 scores → "NEUTRAL" — no directional restriction
+    DISPLAY ONLY — does not gate or block any trade signal anywhere in the system.
+    Top 2 → "STRONG", Bottom 2 → "WEAK", Middle 4 → "NEUTRAL".
 
     Returns:
         {
             "USD": {"direction": "STRONG", "score": 85.2, "rank": 1},
-            "EUR": {"direction": "NEUTRAL", "score": 55.0, "rank": 4},
             "JPY": {"direction": "WEAK", "score": 22.1, "rank": 8},
             ...
         }

ui/confluence_tab.py

@@ -1,16 +1,13 @@
 """
 APEX Confluence Signals Tab — Layer 1 + Layer 2 Merging
 
-Displays:
-- Current Layer 1 fundamental bias
-- Layer 2 technical extremes
-- Confluence signals (both aligned)
-- Risk management details
+DISPLAY ONLY — no position sizing, no auto-execution, no hedging.
+Shows pair, direction, strength/gap, confluence agreement, and text-described zones.
 """
 
 from PyQt5.QtWidgets import (
     QWidget, QVBoxLayout, QHBoxLayout, QLabel, QTableWidget, QTableWidgetItem,
-    QPushButton, QFrame, QMessageBox, QProgressBar
+    QPushButton, QFrame, QHeaderView
 )
 from PyQt5.QtCore import Qt, QTimer
 from PyQt5.QtGui import QColor, QFont
@@ -18,13 +15,12 @@ from typing import Dict, Optional
 from datetime import datetime
 import config
 from layer2_technical import TechnicalAnalyzer
-from confluence_filter import ConfluenceFilter, SignalHistory
-from risk_management import RiskManagementSystem
+from confluence_filter import ConfluenceFilter
 from database import Database
 
 
 class ConfluenceSignalsTab(QWidget):
-    """Confluence signals monitoring and execution."""
+    """Confluence signals monitoring — display only, no execution."""
     
     def __init__(self, db: Database, tech_analyzer: TechnicalAnalyzer):
         super().__init__()
@@ -32,8 +28,6 @@ class ConfluenceSignalsTab(QWidget):
         self.db = db
         self.tech_analyzer = tech_analyzer
         self.confluence = ConfluenceFilter(tech_analyzer, db=db)
-        self.risk_mgmt = RiskManagementSystem(account_balance=config.ACCOUNT_BALANCE)
-        self.signal_history = SignalHistory()
         
         self._init_ui()
         self._setup_auto_refresh()
@@ -61,23 +55,7 @@ class ConfluenceSignalsTab(QWidget):
         
         layout.addWidget(self.signals_table)
         
-        # ====== Risk Management Panel ======
-        risk_layout = QHBoxLayout()
-        risk_layout.addWidget(QLabel("Portfolio Exposure:"))
-        
-        self.exposure_bar = QProgressBar()
-        self.exposure_bar.setMaximum(100)
-        self.exposure_bar.setFormat("%v% exposed")
-        risk_layout.addWidget(self.exposure_bar)
-        
-        self.leverage_label = QLabel("Leverage: —")
-        self.leverage_label.setStyleSheet("font-weight: 600; color: #5d6d7e;")
-        risk_layout.addWidget(self.leverage_label)
-        
-        risk_layout.addStretch()
-        layout.addLayout(risk_layout)
-        
-        # ====== Control Buttons ======
+        # ====== Controls ======
         button_layout = QHBoxLayout()
         
         refresh_btn = QPushButton("Refresh Signals")
@@ -85,11 +63,6 @@ class ConfluenceSignalsTab(QWidget):
         refresh_btn.clicked.connect(self._refresh_signals)
         button_layout.addWidget(refresh_btn)
         
-        execute_btn = QPushButton("Execute Top Signal")
-        execute_btn.setObjectName("success")
-        execute_btn.clicked.connect(self._execute_signal)
-        button_layout.addWidget(execute_btn)
-        
         button_layout.addStretch()
         layout.addLayout(button_layout)
         layout.addStretch()
@@ -234,11 +207,6 @@ class ConfluenceSignalsTab(QWidget):
                 self.confluence_status_label.setText("✕ NO CONFLUENCE")
                 self.confluence_status_label.setStyleSheet("color: #e74c3c; font-weight: bold;")
 
-            portfolio = self.risk_mgmt.get_portfolio_summary()
-            exposure_pct = min((portfolio['total_exposure'] / config.ACCOUNT_BALANCE) * 100, 100)
-            self.exposure_bar.setValue(int(exposure_pct))
-            self.leverage_label.setText(f"Leverage: {portfolio['leverage_ratio']:.2f}x")
-
         except Exception as e:
             print(f"[Confluence] Error refreshing: {e}")
     
@@ -300,55 +268,6 @@ class ConfluenceSignalsTab(QWidget):
 
             row += 1
     
-    def _execute_signal(self):
-        """Execute the top confluence signal."""
-        signals = self.confluence.get_all_signals()
-        if not signals:
-            QMessageBox.warning(self, "No Signal", "No valid confluence signal to execute")
-            return
-
-        try:
-            best = max(signals.values(), key=lambda s: s.get('strength', 0))
-            pair = best['pair']
-            strength = best['strength']
-
-            current_price = 1.0
-
-            trade = self.risk_mgmt.execute_signal(
-                pair,
-                strength,
-                current_price,
-                use_hedging=config.USE_GRID_HEDGING
-            )
-            
-            if trade:
-                msg = (
-                    f"Trade Executed:\n"
-                    f"Pair: {trade['pair']}\n"
-                    f"Entry: {trade['entry_price']:.4f}\n"
-                    f"Size: {trade['position_size']:.2f} lots\n"
-                    f"Confidence: {trade['confluence_strength']:.0f}%"
-                )
-                QMessageBox.information(self, "Trade Executed", msg)
-                
-                self.signal_history.add_signal({
-                    'pair': pair,
-                    'type': best.get('type', 'SIGNAL'),
-                    'entry_price': current_price,
-                    'confluence_strength': strength,
-                })
-            else:
-                QMessageBox.warning(
-                    self,
-                    "Execution Failed",
-                    "Position size would exceed portfolio leverage limits"
-                )
-            
-            self._refresh_signals()
-            
-        except Exception as e:
-            QMessageBox.critical(self, "Error", f"Execution failed: {e}")
-    
     def _setup_auto_refresh(self):
         """Setup automatic refresh timer."""
         self.refresh_timer = QTimer()

ui/dashboard_tab.py

@@ -1,20 +1,11 @@
 """
-APEX Layer 1 — Tab 1: Dashboard
+APEX Dashboard — Tab 1: Primary View
 
-This is the main screen the user sees every day.
+Top section:  LIVE SIGNAL (intraday, from CurrencyStrengthMatrix Z-scores)
+Bottom section: MACRO BACKDROP (monthly, from scorer.py fundamental data)
 
-Features:
-- Signal card at top (shows PRIMARY SIGNAL, gap, status, updated date)
-- Ranked score table below with all 8 currencies
-- Strongest row highlighted GREEN (BUY)
-- Weakest row highlighted RED (SELL)
-- Score bar charts per row (visual progress)
-- Auto-refresh when data updated from Entry tab or FRED API
-
-Display:
-- Rank, Currency, Rate, CPI, PMI, Score columns
-- Color-coded rows, "BUY" and "SELL" tags
-- Last updated timestamp
+The live signal is the primary trading reference. Macro Backdrop is slow-moving
+context for display only.
 """
 
 from PyQt5.QtWidgets import (
@@ -27,29 +18,34 @@ from typing import Dict, Optional
 from datetime import datetime
 import config
 from database import Database
+from currency_strength_matrix import CurrencyStrengthMatrix
+from layer2_technical import TechnicalAnalyzer
 import scorer
 
 
 class DashboardTab(QWidget):
-    """Main dashboard showing current signal and currency rankings."""
+    """Dashboard: live intraday signal (CurrencyStrengthMatrix) + macro backdrop (scorer)."""
     
     # Signal to request FRED fetch
     fetch_rates_requested = pyqtSignal()
     
     # Signal emitted when new signal generated (for Layer 2 confluence)
-    # Emits: strongest, weakest, gap, directional_bias_matrix
     signal_generated = pyqtSignal(str, str, float, dict)
     
-    def __init__(self, db: Database):
+    def __init__(self, db: Database, tech_analyzer: TechnicalAnalyzer = None):
         """
         Initialize Dashboard tab.
         
         Args:
             db: Database instance
+            tech_analyzer: TechnicalAnalyzer instance for live signal data
         """
         super().__init__()
         self.db = db
+        self.tech_analyzer = tech_analyzer or TechnicalAnalyzer()
+        self.matrix = CurrencyStrengthMatrix()
         self.current_month = datetime.now().strftime("%Y-%m")
+        self._last_matrix_report = None
         
         self._init_ui()
         self._refresh_display()
@@ -59,12 +55,16 @@ class DashboardTab(QWidget):
         layout = QVBoxLayout()
         layout.setSpacing(12)
         
-        # ====== Signal Card ======
-        signal_card = self._build_signal_card()
-        layout.addWidget(signal_card)
+        # ====== Live Signal Card (intraday, from CurrencyStrengthMatrix) ======
+        live_card = self._build_live_signal_card()
+        layout.addWidget(live_card)
         
-        # ====== Ranked Score Table ======
-        heading = QLabel("Currency Rankings")
+        # ====== Macro Backdrop Card (monthly, from scorer.py) ======
+        backdrop_card = self._build_macro_backdrop_card()
+        layout.addWidget(backdrop_card)
+        
+        # ====== Ranked Score Table (Macro Backdrop detail) ======
+        heading = QLabel("Macro Backdrop — Currency Rankings")
         heading.setProperty("heading", True)
         layout.addWidget(heading)
         
@@ -119,36 +119,77 @@ class DashboardTab(QWidget):
         
         self.setLayout(layout)
     
-    def _build_signal_card(self) -> QFrame:
-        """Build the signal card frame."""
+    def _build_live_signal_card(self) -> QFrame:
+        """Build the live intraday signal card (from CurrencyStrengthMatrix)."""
         card = QFrame()
         card.setObjectName("statusCard")
+
+        layout = QVBoxLayout()
+        layout.setSpacing(6)
+
+        title = QLabel("LIVE SIGNAL (Intraday)")
+        title.setProperty("subheading", True)
+        layout.addWidget(title)
+
+        # Matrix Cross pair (largest divergence)
+        self.live_signal_label = QLabel("Waiting for Layer 2 data...")
+        self.live_signal_label.setProperty("value", True)
+        self.live_signal_label.setStyleSheet("color: #2c3e50;")
+        layout.addWidget(self.live_signal_label)
+
+        # Divergence gap
+        self.live_gap_label = QLabel("Divergence: — σ")
+        self.live_gap_label.setStyleSheet("font-size: 15px; color: #5d6d7e;")
+        layout.addWidget(self.live_gap_label)
+
+        # Matrix ranked currencies (top/bottom 2)
+        self.live_ranked_label = QLabel("")
+        self.live_ranked_label.setStyleSheet("font-size: 13px; color: #7f8c8d;")
+        layout.addWidget(self.live_ranked_label)
+
+        # Session + SRV
+        self.live_session_label = QLabel("Session: —  |  SRV: —")
+        self.live_session_label.setStyleSheet("font-size: 12px; color: #95a5a6;")
+        layout.addWidget(self.live_session_label)
+
+        # Entry zones (SL/TP text-described, not executable)
+        self.live_entry_zones = QLabel("")
+        self.live_entry_zones.setStyleSheet("font-size: 12px; color: #8e44ad;")
+        layout.addWidget(self.live_entry_zones)
+
+        # Updated timestamp
+        self.live_updated_label = QLabel("Updated: —")
+        self.live_updated_label.setStyleSheet("color: #95a5a6; font-size: 12px;")
+        layout.addWidget(self.live_updated_label)
+
+        layout.addStretch()
+        card.setLayout(layout)
+        return card
+
+    def _build_macro_backdrop_card(self) -> QFrame:
+        """Build the macro backdrop card frame (from scorer.py fundamental data)."""
+        card = QFrame()
+        card.setObjectName("card")
         
         layout = QVBoxLayout()
         layout.setSpacing(6)
         
-        # Title
-        title = QLabel("PRIMARY SIGNAL")
+        title = QLabel("MACRO BACKDROP (Fundamental — slow context)")
         title.setProperty("subheading", True)
         layout.addWidget(title)
         
-        # Signal text (large, bold)
-        self.signal_label = QLabel("NO TRADE — Initializing...")
-        self.signal_label.setProperty("value", True)
-        self.signal_label.setStyleSheet("color: #2c3e50;")
-        layout.addWidget(self.signal_label)
+        self.macro_signal_label = QLabel("NO TRADE — Initializing...")
+        self.macro_signal_label.setStyleSheet("font-size: 18px; font-weight: 600; color: #2c3e50;")
+        layout.addWidget(self.macro_signal_label)
         
-        # Gap and status
-        self.gap_label = QLabel("Gap: — points")
-        self.gap_label.setStyleSheet("font-size: 15px; color: #5d6d7e;")
-        layout.addWidget(self.gap_label)
+        self.macro_gap_label = QLabel("Gap: — points")
+        self.macro_gap_label.setStyleSheet("font-size: 13px; color: #5d6d7e;")
+        layout.addWidget(self.macro_gap_label)
         
-        # Updated timestamp
-        self.updated_label = QLabel("Updated: —")
-        self.updated_label.setStyleSheet("color: #95a5a6; font-size: 12px;")
-        layout.addWidget(self.updated_label)
+        self.macro_updated_label = QLabel("Updated: —")
+        self.macro_updated_label.setStyleSheet("color: #95a5a6; font-size: 12px;")
+        layout.addWidget(self.macro_updated_label)
         
-        # Staleness warning (hidden by default)
         self.stale_warning = QLabel("")
         self.stale_warning.setStyleSheet(
             "color: #e74c3c; font-weight: 700; font-size: 13px; padding: 6px 0;"
@@ -161,9 +202,8 @@ class DashboardTab(QWidget):
         return card
     
     def _refresh_display(self):
-        """Refresh dashboard with latest data."""
+        """Refresh macro backdrop with latest fundamental data."""
         try:
-            # Get signal for current month
             signal_data = self.db.get_signal(self.current_month)
             
             if signal_data:
@@ -173,7 +213,6 @@ class DashboardTab(QWidget):
                 strongest = signal_data.get("strongest")
                 weakest = signal_data.get("weakest")
 
-                # Build directional bias matrix and emit to confluence tab
                 if strongest and weakest:
                     scores = self.db.get_month_scores(self.current_month)
                     if scores:
@@ -182,13 +221,10 @@ class DashboardTab(QWidget):
                         bias_matrix = {}
                     self.signal_generated.emit(strongest, weakest, gap, bias_matrix)
                 
-                self.signal_label.setText(signal_text)
-                if status == "ACTIVE":
-                    self.signal_label.setStyleSheet("color: #27ae60;")
-                else:
-                    self.signal_label.setStyleSheet("color: #e74c3c;")
+                self.macro_signal_label.setText(signal_text)
+                color = "#27ae60" if status == "ACTIVE" else "#e74c3c"
+                self.macro_signal_label.setStyleSheet(f"font-size: 18px; font-weight: 600; color: {color};")
                 
-                # Update gap label
                 gap_tier = scorer.get_gap_tier(gap)
                 tier_name = {
                     "no_trade": "Too narrow",
@@ -197,26 +233,112 @@ class DashboardTab(QWidget):
                     "strong": "Strong signal"
                 }.get(gap_tier, "Unknown")
                 
-                self.gap_label.setText(f"Gap: {gap:.1f} points · {tier_name}")
+                self.macro_gap_label.setText(f"Gap: {gap:.1f} points · {tier_name}")
             else:
-                self.signal_label.setText("NO TRADE — No data yet")
-                self.signal_label.setStyleSheet("color: #e74c3c;")
-                self.gap_label.setText("Gap: — points")
+                self.macro_signal_label.setText("NO TRADE — No data yet")
+                self.macro_signal_label.setStyleSheet("font-size: 18px; font-weight: 600; color: #e74c3c;")
+                self.macro_gap_label.setText("Gap: — points")
             
-            # Update timestamp
-            self.updated_label.setText(f"Updated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
+            self.macro_updated_label.setText(f"Updated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
             
-            # Check for stale CPI/PMI data
             self._check_data_staleness()
-            
-            # Refresh score table
             self._refresh_score_table()
             
         except Exception as e:
             print(f"[ERROR] Failed to refresh dashboard: {e}")
-            self.signal_label.setText("ERROR")
-            self.signal_label.setStyleSheet("color: #e74c3c;")
+            self.macro_signal_label.setText("ERROR")
+            self.macro_signal_label.setStyleSheet("font-size: 18px; font-weight: 600; color: #e74c3c;")
     
+    def _refresh_live_signal(self):
+        """Refresh the live intraday signal from CurrencyStrengthMatrix."""
+        try:
+            z_scores = self.tech_analyzer.get_all_z_scores()
+            if not z_scores:
+                self.live_signal_label.setText("Waiting for Layer 2 data...")
+                self.live_signal_label.setStyleSheet("font-size: 28px; font-weight: 700; color: #95a5a6;")
+                self.live_gap_label.setText("Divergence: — σ")
+                self.live_ranked_label.setText("")
+                self.live_session_label.setText("Session: —  |  SRV: —")
+                self.live_entry_zones.setText("")
+                return
+
+            current_prices = {}
+            for pair in z_scores:
+                lp = self.tech_analyzer.get_last_price(pair)
+                if lp is not None:
+                    current_prices[pair] = lp
+
+            self.matrix.update(z_scores, current_prices=current_prices)
+            report = self.matrix.get_report()
+            self._last_matrix_report = report
+
+            mc = report.get("matrix_cross")
+            gap = report.get("divergence_gap", 0)
+            has_div = report.get("has_divergence", False)
+            ranked = report.get("ranked", [])
+
+            if mc and mc != "N/A":
+                signal_text = mc
+                color = "#e74c3c" if has_div else "#2c3e50"
+                self.live_signal_label.setText(signal_text)
+                self.live_signal_label.setStyleSheet(f"font-size: 28px; font-weight: 700; color: {color};")
+                self.live_gap_label.setText(f"Divergence: {gap:.2f}σ{' — EXTREME' if has_div else ''}")
+            else:
+                self.live_signal_label.setText("No divergence")
+                self.live_signal_label.setStyleSheet("font-size: 28px; font-weight: 700; color: #95a5a6;")
+                self.live_gap_label.setText("Divergence: — σ")
+
+            if ranked:
+                top2 = [f"{c[0]}({c[1]:+.1f}σ)" for c in ranked[:2]]
+                bot2 = [f"{c[0]}({c[1]:+.1f}σ)" for c in ranked[-2:]]
+                self.live_ranked_label.setText(
+                    f"Strongest: {'  '.join(top2)}  |  Weakest: {'  '.join(bot2)}"
+                )
+            else:
+                self.live_ranked_label.setText("")
+
+            session = report.get("active_session", "—")
+            srv_data = self.matrix.get_srv_map()
+            srv_parts = []
+            if srv_data:
+                for ccy in ranked[:3]:
+                    name = ccy[0]
+                    if name in srv_data:
+                        s = srv_data[name]
+                        sign = "+" if s >= 0 else ""
+                        srv_parts.append(f"{name}: {sign}{s:.3f}%")
+            srv_str = "  |  ".join(srv_parts)
+            self.live_session_label.setText(
+                f"Session: {session}  |  SRV: {srv_str}" if srv_str
+                else f"Session: {session}  |  SRV: —"
+            )
+
+            # Text-described entry zones (advisory only, no position sizing)
+            entry_parts = []
+            if mc and mc != "N/A":
+                entry_price = self.tech_analyzer.get_last_price(mc)
+                if entry_price:
+                    sl_tp = self.tech_analyzer.calculate_sl_tp(
+                        mc, "LONG" if has_div else "SHORT", entry_price
+                    )
+                    if sl_tp.get("sl") and sl_tp.get("tp"):
+                        entry_parts.append(
+                            f"Entry zones — {mc}: ~{entry_price:.5f} "
+                            f"(SL: {sl_tp['sl']:.5f}, TP: {sl_tp['tp']:.5f})"
+                        )
+            self.live_entry_zones.setText("  |  ".join(entry_parts))
+
+            self.live_updated_label.setText(
+                f"Updated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
+            )
+
+        except Exception as e:
+            print(f"[Dashboard] Live signal error: {e}")
+
+    def update_live_signal(self):
+        """Called externally to trigger live signal refresh."""
+        self._refresh_live_signal()
+
     def _check_data_staleness(self):
         """Show a warning if CPI/PMI data is older than 35 days."""
         try:

ui/layer2_monitor_tab.py

@@ -407,7 +407,7 @@ class Layer2MonitorTab(QWidget):
                 z_item.setFlags(z_item.flags() & ~Qt.ItemIsEditable)
                 z_item.setTextAlignment(Qt.AlignCenter)
 
-                if abs(z_score) >= config.Z_SCORE_THRESHOLD:
+                if abs(z_score) >= config.SCALP_Z_SCORE_THRESHOLD:
                     z_item.setBackground(QColor("#ffebee"))
                     z_item.setForeground(QColor("#c62828"))
 
@@ -525,7 +525,7 @@ class Layer2MonitorTab(QWidget):
                 z_item.setTextAlignment(Qt.AlignCenter)
 
                 # High-contrast σ formatting (Task 4.1)
-                threshold = config.Z_SCORE_THRESHOLD
+                threshold = config.SCALP_Z_SCORE_THRESHOLD
                 if z_val >= threshold:
                     z_item.setBackground(QColor("#c62828"))
                     z_item.setForeground(QColor("white"))