feat: Implement Equity Curve Trading for automatic drawdown protection

NEW MODULE: equity_curve_trading.py
- EquityCurveManager class for meta-strategy control
- Tracks equity history after each trade
- Calculates Moving Average over configurable period (default: 10 trades)
- Soft Mode: Reduces lot size to 50% when equity < MA
- Hard Mode: Completely stops trading when equity < MA
- Recovery detection with buffer percentage
- Persistent storage in equity_curve_history.json

CONFIGURATION:
- ma_period: 10 trades (Moving Average window)
- min_trades_required: 5 (warmup period)
- soft_mode: True (reduce lots instead of stopping)
- soft_mode_multiplier: 0.5 (50% lots when under MA)
- recovery_buffer_pct: 0.5% (buffer for recovery status)

INTEGRATION:
- Added to Cell 78 (Advanced Optimizations setup)
- Integrated in enhanced_trading_check_wrapper (Cells 85, 90)
- Added lot_multiplier parameter to execute_trade_v2_adaptive
- Equity update after each successful trade

EXAMPLE FLOW:
1. Before trade: Check should_trade() → returns (allowed, reason, lot_multiplier)
2. If equity < MA: lot_multiplier = 0.5 (or 0.0 in hard mode)
3. Position size adjusted: volume = volume * lot_multiplier
4. After trade: update_equity() called to track new equity

BENEFITS:
- Automatic protection during losing streaks
- Reduces exposure when strategy underperforms
- Capitalizes fully when strategy is working
- No emotional decisions needed

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

activate_enhanced_scoring.py

@@ -66,6 +66,14 @@ def enhanced_trading_check_wrapper(symbol="XAUUSD", debug=False):
 
         print(f"✅ Position-Check OK: {position_info['count']}/{max_positions}")
 
+        # SCHRITT 1.5: EQUITY CURVE CHECK
+        ec_allowed, ec_reason, lot_multiplier = equity_curve_manager.should_trade()
+        print(f"📈 Equity Curve: {ec_reason}")
+
+        if not ec_allowed:
+            print(f"⛔ TRADE BLOCKIERT durch Equity Curve Filter")
+            return None
+
         # SCHRITT 2: Signal Analysis (wie vorher)
         signal_info = extended_top_down_v2_adaptive(symbol)
         if signal_info is None:
@@ -127,9 +135,15 @@ def enhanced_trading_check_wrapper(symbol="XAUUSD", debug=False):
                 result = execute_trade_v2_adaptive(
                     symbol=symbol,
                     signal_info_override=signal_info,
-                    confidence_override=final_confidence  # ← Use hybrid score!
+                    confidence_override=final_confidence,  # ← Use hybrid score!
+                    lot_multiplier=lot_multiplier  # ← Equity Curve adjustment
                 )
 
+                # Update Equity Curve nach Trade
+                if result is not None:
+                    equity_curve_manager.update_equity()
+                    print(f"📈 Equity Curve updated")
+
                 return result
             else:
                 print(f"\\n❌ Signal below threshold: {final_confidence:.1f}% < {adaptive_threshold:.1f}%")