Update app.py

app.py

@@ -1,4 +1,4 @@
-# app.py (Updated to V8.6 - Vader + ndarray Fix)
+# app.py (Updated to V8.7 - MC Expected Return Fix)
 import os
 import traceback
 import signal
@@ -270,7 +270,7 @@ async def process_batch_parallel(batch, ml_processor, batch_num, total_batches,
 
 async def run_3_layer_analysis_explorer() -> List[Dict[str, Any]]:
     """
-    (معدل V8.2) - استخدام درجة الأخبار الإحصائية
+    (معدل V8.7) - إصلاح العائد المتوقع (Expected Return)
     """
     layer1_candidates = []
     layer2_candidates = []
@@ -446,6 +446,23 @@ async def run_3_layer_analysis_explorer() -> List[Dict[str, Any]]:
                     candidate.get('ohlcv')
                 )
                 if advanced_mc_results and advanced_mc_results.get('simulation_model') == 'Phase2_GARCH_LGBM':
+                    
+                    # 🔴 --- START OF CHANGE (V8.7 - MC Expected Return Fix) --- 🔴
+                    # (إصلاح: حساب العائد المتوقع يدوياً إذا كان مفقوداً)
+                    if 'expected_return_pct' not in advanced_mc_results:
+                        try:
+                            mean_price = advanced_mc_results.get('distribution_summary', {}).get('mean_price', 0)
+                            current_price = advanced_mc_results.get('current_price', 0)
+                            if mean_price > 0 and current_price > 0:
+                                expected_return_pct = (mean_price - current_price) / current_price
+                                advanced_mc_results['expected_return_pct'] = expected_return_pct
+                                print(f"      [MC Patch] {symbol}: Calculated Expected Return: {expected_return_pct:+.2%}")
+                            else:
+                                advanced_mc_results['expected_return_pct'] = 0.0
+                        except Exception:
+                            advanced_mc_results['expected_return_pct'] = 0.0
+                    # 🔴 --- END OF CHANGE --- 🔴
+
                     candidate['monte_carlo_distribution'] = advanced_mc_results
                     candidate['monte_carlo_probability'] = advanced_mc_results.get('probability_of_gain', 0)
                     candidate['advanced_mc_run'] = True
@@ -549,7 +566,7 @@ async def run_3_layer_analysis_explorer() -> List[Dict[str, Any]]:
 
 
 async def re_analyze_open_trade_async(trade_data):
-    """(V8.6) إضافة إصلاح ndarray"""
+    """(V8.7) إضافة إصلاح ndarray + إصلاح العائد المتوقع"""
     symbol = trade_data.get('symbol')
     try:
         async with state_manager.trade_analysis_lock:
@@ -595,6 +612,23 @@ async def re_analyze_open_trade_async(trade_data):
             if not processed_data: return None
 
             if advanced_mc_results:
+                
+                # 🔴 --- START OF CHANGE (V8.7 - MC Expected Return Fix) --- 🔴
+                # (إصلاح: حساب العائد المتوقع يدوياً إذا كان مفقوداً)
+                if 'expected_return_pct' not in advanced_mc_results:
+                    try:
+                        mean_price = advanced_mc_results.get('distribution_summary', {}).get('mean_price', 0)
+                        current_price = advanced_mc_results.get('current_price', 0)
+                        if mean_price > 0 and current_price > 0:
+                            expected_return_pct = (mean_price - current_price) / current_price
+                            advanced_mc_results['expected_return_pct'] = expected_return_pct
+                            print(f"      [MC Patch] {symbol}: Calculated Expected Return: {expected_return_pct:+.2%}")
+                        else:
+                            advanced_mc_results['expected_return_pct'] = 0.0
+                    except Exception:
+                        advanced_mc_results['expected_return_pct'] = 0.0
+                # 🔴 --- END OF CHANGE --- 🔴
+
                 processed_data['monte_carlo_distribution'] = advanced_mc_results
                 processed_data['monte_carlo_probability'] = advanced_mc_results.get('probability_of_gain', 0)