diff --git a/_dev/cleanup_models_now.py b/_dev/cleanup_models_now.py
deleted file mode 100644
index 2fc94c0..0000000
--- a/_dev/cleanup_models_now.py
+++ /dev/null
@@ -1,98 +0,0 @@
-#!/usr/bin/env python3
-"""
-Immediate Model Cleanup Script
-
-This script will clean up all existing model files and prepare the system
-for fresh training with the new model management system.
-"""
-
-import logging
-import sys
-from model_manager import ModelManager
-
-def main():
-    """Run the model cleanup"""
-    
-    # Configure logging for better output
-    logging.basicConfig(
-        level=logging.INFO,
-        format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
-    )
-    
-    print("=" * 60)
-    print("GOGO2 MODEL CLEANUP SYSTEM")
-    print("=" * 60)
-    print()
-    print("This script will:")
-    print("1. Delete ALL existing model files (.pt, .pth)")
-    print("2. Remove ALL checkpoint directories")
-    print("3. Clear model backup directories")
-    print("4. Reset the model registry")
-    print("5. Create clean directory structure")
-    print()
-    print("WARNING: This action cannot be undone!")
-    print()
-    
-    # Calculate current space usage first
-    try:
-        manager = ModelManager()
-        storage_stats = manager.get_storage_stats()
-        print(f"Current storage usage:")
-        print(f"- Models: {storage_stats['total_models']}")
-        print(f"- Size: {storage_stats['actual_size_mb']:.1f}MB")
-        print()
-    except Exception as e:
-        print(f"Error checking current storage: {e}")
-        print()
-    
-    # Ask for confirmation
-    print("Type 'CLEANUP' to proceed with the cleanup:")
-    user_input = input("> ").strip()
-    
-    if user_input != "CLEANUP":
-        print("Cleanup cancelled. No changes made.")
-        return
-    
-    print()
-    print("Starting cleanup...")
-    print("-" * 40)
-    
-    try:
-        # Create manager and run cleanup
-        manager = ModelManager()
-        cleanup_result = manager.cleanup_all_existing_models(confirm=True)
-        
-        print()
-        print("=" * 60)
-        print("CLEANUP COMPLETE")
-        print("=" * 60)
-        print(f"Files deleted: {cleanup_result['deleted_files']}")
-        print(f"Space freed: {cleanup_result['freed_space_mb']:.1f} MB")
-        print(f"Directories cleaned: {len(cleanup_result['deleted_directories'])}")
-        
-        if cleanup_result['errors']:
-            print(f"Errors encountered: {len(cleanup_result['errors'])}")
-            print("Errors:")
-            for error in cleanup_result['errors'][:5]:  # Show first 5 errors
-                print(f"  - {error}")
-            if len(cleanup_result['errors']) > 5:
-                print(f"  ... and {len(cleanup_result['errors']) - 5} more")
-        
-        print()
-        print("System is now ready for fresh model training!")
-        print("The following directories have been created:")
-        print("- models/best_models/")
-        print("- models/cnn/")
-        print("- models/rl/")
-        print("- models/checkpoints/")
-        print("- NN/models/saved/")
-        print()
-        print("New models will be automatically managed by the ModelManager.")
-        
-    except Exception as e:
-        print(f"Error during cleanup: {e}")
-        logging.exception("Cleanup failed")
-        sys.exit(1)
-
-if __name__ == "__main__":
-    main() 
\ No newline at end of file
diff --git a/check_data_stream_status.py b/check_data_stream_status.py
deleted file mode 100644
index e7506fa..0000000
--- a/check_data_stream_status.py
+++ /dev/null
@@ -1,71 +0,0 @@
-#!/usr/bin/env python3
-"""
-Data Stream Status Checker
-
-This script provides better information about the data stream status
-when the dashboard is running.
-"""
-
-import requests
-import json
-import time
-from datetime import datetime
-
-def check_dashboard_status():
-    """Check if dashboard is running and get basic status"""
-    try:
-        response = requests.get('http://127.0.0.1:8050', timeout=3)
-        if response.status_code == 200:
-            return True, "Dashboard is running"
-        else:
-            return False, f"Dashboard responded with status {response.status_code}"
-    except requests.exceptions.ConnectionError:
-        return False, "Dashboard not running (connection refused)"
-    except Exception as e:
-        return False, f"Error checking dashboard: {e}"
-
-def main():
-    print("🔍 Data Stream Status Check")
-    print("=" * 50)
-    
-    # Check if dashboard is running
-    dashboard_running, dashboard_msg = check_dashboard_status()
-    
-    if dashboard_running:
-        print("✅ Dashboard Status: RUNNING")
-        print(f"   URL: http://127.0.0.1:8050")
-        print(f"   Message: {dashboard_msg}")
-        print()
-        print("📊 Data Stream Information:")
-        print("   The data stream monitor is running inside the dashboard process.")
-        print("   You should see data stream output in the dashboard console.")
-        print()
-        print("🔧 How to Access Data Stream:")
-        print("   1. Check the dashboard console output for data stream samples")
-        print("   2. The dashboard automatically starts data streaming")
-        print("   3. Data is being collected and displayed in real-time")
-        print()
-        print("📝 Expected Console Output (in dashboard terminal):")
-        print("   =================================================")
-        print("   DATA STREAM SAMPLE - 16:10:30")
-        print("   =================================================")
-        print("   OHLCV (1m): ETH/USDT | O:4335.67 H:4338.92 L:4334.21 C:4336.67 V:125.8")
-        print("   TICK: ETH/USDT | Price:4336.67 Vol:0.0456 Side:buy")
-        print("   MODEL: DQN | Conf:0.78 Pred:BUY Loss:0.0234")
-        print("   =================================================")
-        print()
-        print("💡 Note: The data_stream_control.py script cannot access the")
-        print("   dashboard's data stream due to process isolation.")
-        print("   The data stream is active and working within the dashboard.")
-        
-    else:
-        print("❌ Dashboard Status: NOT RUNNING")
-        print(f"   Error: {dashboard_msg}")
-        print()
-        print("🔧 To start the dashboard:")
-        print("   python run_clean_dashboard.py")
-        print()
-        print("   Then check this status again.")
-
-if __name__ == "__main__":
-    main()
diff --git a/debug/test_fixed_issues.py b/debug/test_fixed_issues.py
index e4bc8f6..e157394 100644
--- a/debug/test_fixed_issues.py
+++ b/debug/test_fixed_issues.py
@@ -70,70 +70,11 @@ def test_trading_statistics():
     logger.info(f"   Avg losing trade: ${daily_stats.get('avg_losing_trade', 0.0):.2f}")
     logger.info(f"   Total P&L: ${daily_stats.get('total_pnl', 0.0):.2f}")
     
-    # Simulate some trades if we don't have any
+    # If no trades, we can't test calculations
     if daily_stats.get('total_trades', 0) == 0:
-        logger.info("3. No trades found - simulating some test trades...")
-        
-        # Add some mock trades to the trade history
-        from core.trading_executor import TradeRecord
-        from datetime import datetime
-        
-        # Add a winning trade
-        winning_trade = TradeRecord(
-            symbol='ETH/USDT',
-            side='LONG',
-            quantity=0.01,
-            entry_price=2500.0,
-            exit_price=2550.0,
-            entry_time=datetime.now(),
-            exit_time=datetime.now(),
-            pnl=0.50,  # $0.50 profit
-            fees=0.01,
-            confidence=0.8
-        )
-        trading_executor.trade_history.append(winning_trade)
-        
-        # Add a losing trade
-        losing_trade = TradeRecord(
-            symbol='ETH/USDT',
-            side='LONG',
-            quantity=0.01,
-            entry_price=2500.0,
-            exit_price=2480.0,
-            entry_time=datetime.now(),
-            exit_time=datetime.now(),
-            pnl=-0.20,  # $0.20 loss
-            fees=0.01,
-            confidence=0.7
-        )
-        trading_executor.trade_history.append(losing_trade)
-        
-        # Get updated stats
-        daily_stats = trading_executor.get_daily_stats()
-        logger.info("   Updated statistics after adding test trades:")
-        logger.info(f"   Total trades: {daily_stats.get('total_trades', 0)}")
-        logger.info(f"   Winning trades: {daily_stats.get('winning_trades', 0)}")
-        logger.info(f"   Losing trades: {daily_stats.get('losing_trades', 0)}")
-        logger.info(f"   Win rate: {daily_stats.get('win_rate', 0.0) * 100:.1f}%")
-        logger.info(f"   Avg winning trade: ${daily_stats.get('avg_winning_trade', 0.0):.2f}")
-        logger.info(f"   Avg losing trade: ${daily_stats.get('avg_losing_trade', 0.0):.2f}")
-        logger.info(f"   Total P&L: ${daily_stats.get('total_pnl', 0.0):.2f}")
-        
-        # Verify calculations
-        expected_win_rate = 1/2  # 1 win out of 2 trades = 50%
-        expected_avg_win = 0.50
-        expected_avg_loss = -0.20
-        
-        actual_win_rate = daily_stats.get('win_rate', 0.0)
-        actual_avg_win = daily_stats.get('avg_winning_trade', 0.0)
-        actual_avg_loss = daily_stats.get('avg_losing_trade', 0.0)
-        
-        logger.info("4. Verifying calculations:")
-        logger.info(f"   Win rate: Expected {expected_win_rate*100:.1f}%, Got {actual_win_rate*100:.1f}% ✅" if abs(actual_win_rate - expected_win_rate) < 0.01 else f"   Win rate: Expected {expected_win_rate*100:.1f}%, Got {actual_win_rate*100:.1f}% ❌")
-        logger.info(f"   Avg win: Expected ${expected_avg_win:.2f}, Got ${actual_avg_win:.2f} ✅" if abs(actual_avg_win - expected_avg_win) < 0.01 else f"   Avg win: Expected ${expected_avg_win:.2f}, Got ${actual_avg_win:.2f} ❌")
-        logger.info(f"   Avg loss: Expected ${expected_avg_loss:.2f}, Got ${actual_avg_loss:.2f} ✅" if abs(actual_avg_loss - expected_avg_loss) < 0.01 else f"   Avg loss: Expected ${expected_avg_loss:.2f}, Got ${actual_avg_loss:.2f} ❌")
-        
-        return True
+        logger.info("3. No trades found - cannot test calculations without real trading data")
+        logger.info("   Run the system and execute some real trades to test statistics")
+        return False
     
     return True
 
diff --git a/debug/test_trading_fixes.py b/debug/test_trading_fixes.py
index 79eca49..7230511 100644
--- a/debug/test_trading_fixes.py
+++ b/debug/test_trading_fixes.py
@@ -84,52 +84,10 @@ def test_win_rate_calculation():
     
     trading_executor = TradingExecutor()
     
-    # Clear existing trades
-    trading_executor.trade_history = []
-    
-    # Add test trades with meaningful P&L
-    logger.info("1. Adding test trades with meaningful P&L:")
-    
-    # Add 3 winning trades
-    for i in range(3):
-        winning_trade = TradeRecord(
-            symbol='ETH/USDT',
-            side='LONG',
-            quantity=1.0,
-            entry_price=2500.0,
-            exit_price=2550.0,
-            entry_time=datetime.now(),
-            exit_time=datetime.now(),
-            pnl=50.0,  # $50 profit with leverage
-            fees=1.0,
-            confidence=0.8,
-            hold_time_seconds=30.0  # 30 second hold
-        )
-        trading_executor.trade_history.append(winning_trade)
-        logger.info(f"   Added winning trade #{i+1}: +$50.00 (30s hold)")
-    
-    # Add 2 losing trades
-    for i in range(2):
-        losing_trade = TradeRecord(
-            symbol='ETH/USDT',
-            side='LONG',
-            quantity=1.0,
-            entry_price=2500.0,
-            exit_price=2475.0,
-            entry_time=datetime.now(),
-            exit_time=datetime.now(),
-            pnl=-25.0,  # $25 loss with leverage
-            fees=1.0,
-            confidence=0.7,
-            hold_time_seconds=15.0  # 15 second hold
-        )
-        trading_executor.trade_history.append(losing_trade)
-        logger.info(f"   Added losing trade #{i+1}: -$25.00 (15s hold)")
-    
-    # Get statistics
+    # Get statistics from existing trades
     stats = trading_executor.get_daily_stats()
-    
-    logger.info("2. Calculated statistics:")
+
+    logger.info("1. Current trading statistics:")
     logger.info(f"   Total trades: {stats['total_trades']}")
     logger.info(f"   Winning trades: {stats['winning_trades']}")
     logger.info(f"   Losing trades: {stats['losing_trades']}")
@@ -137,21 +95,23 @@ def test_win_rate_calculation():
     logger.info(f"   Avg winning trade: ${stats['avg_winning_trade']:.2f}")
     logger.info(f"   Avg losing trade: ${stats['avg_losing_trade']:.2f}")
     logger.info(f"   Total P&L: ${stats['total_pnl']:.2f}")
-    
-    # Verify calculations
-    expected_win_rate = 3/5  # 3 wins out of 5 trades = 60%
-    expected_avg_win = 50.0
-    expected_avg_loss = -25.0
-    
-    logger.info("3. Verification:")
-    win_rate_ok = abs(stats['win_rate'] - expected_win_rate) < 0.01
-    avg_win_ok = abs(stats['avg_winning_trade'] - expected_avg_win) < 0.01
-    avg_loss_ok = abs(stats['avg_losing_trade'] - expected_avg_loss) < 0.01
-    
-    logger.info(f"   Win rate: Expected {expected_win_rate*100:.1f}%, Got {stats['win_rate']*100:.1f}% {'✅' if win_rate_ok else '❌'}")
-    logger.info(f"   Avg win: Expected ${expected_avg_win:.2f}, Got ${stats['avg_winning_trade']:.2f} {'✅' if avg_win_ok else '❌'}")
-    logger.info(f"   Avg loss: Expected ${expected_avg_loss:.2f}, Got ${stats['avg_losing_trade']:.2f} {'✅' if avg_loss_ok else '❌'}")
-    
+
+    # If no trades, we can't verify calculations
+    if stats['total_trades'] == 0:
+        logger.info("2. No trades found - cannot verify calculations")
+        logger.info("   Run the system and execute real trades to test statistics")
+        return False
+
+    # Basic sanity checks on existing data
+    logger.info("2. Basic validation:")
+    win_rate_ok = 0.0 <= stats['win_rate'] <= 1.0
+    avg_win_ok = stats['avg_winning_trade'] >= 0 if stats['winning_trades'] > 0 else True
+    avg_loss_ok = stats['avg_losing_trade'] <= 0 if stats['losing_trades'] > 0 else True
+
+    logger.info(f"   Win rate in valid range [0,1]: {'✅' if win_rate_ok else '❌'}")
+    logger.info(f"   Avg win is positive when winning trades exist: {'✅' if avg_win_ok else '❌'}")
+    logger.info(f"   Avg loss is negative when losing trades exist: {'✅' if avg_loss_ok else '❌'}")
+
     return win_rate_ok and avg_win_ok and avg_loss_ok
 
 def test_new_features():
diff --git a/scripts/start_live_trading.ps1 b/scripts/start_live_trading.ps1
index 51ba20c..2402f57 100644
--- a/scripts/start_live_trading.ps1
+++ b/scripts/start_live_trading.ps1
@@ -9,6 +9,6 @@ Start-Process powershell -ArgumentList "-Command python run_tensorboard.py" -Win
 Write-Host "Starting TensorBoard... Please wait" -ForegroundColor Yellow
 Start-Sleep -Seconds 5
 
-# Start the live trading demo in the current window
-Write-Host "Starting Live Trading Demo with mock data..." -ForegroundColor Green
-python run_live_demo.py --symbol ETH/USDT --timeframe 1m --model models/trading_agent_best_pnl.pt --mock 
\ No newline at end of file
+# Start the live trading system in the current window
+Write-Host "Starting Live Trading System..." -ForegroundColor Green
+python main_clean.py --port 8051 
\ No newline at end of file