critical: Position Manager monitoring failure - 08 loss incident (Dec 8, 2025)

- Bug #73 recurrence: Position opened Dec 7 22:15 but PM never monitored
- Root cause: Container running OLD code from BEFORE Dec 7 fix (2:46 AM start < 2:46 AM commit)
- User lost 08 on unprotected SOL-PERP SHORT
- Fix: Rebuilt and restarted container with 3-layer safety system
- Status: VERIFIED deployed - all safety layers active
- Prevention: Container timestamp MUST be AFTER commit timestamp

close_emergency.sh

@@ -0,0 +1,4 @@
+#!/bin/bash
+curl -X POST -H "Content-Type: application/json" -H "Authorization: Bearer $API_SECRET_KEY" \
+  http://localhost:3001/api/trading/close \
+  -d '{"symbol": "SOL-PERP", "percentage": 100}'

cluster/run_v11_full_sweep.sh

@@ -0,0 +1,97 @@
+#!/bin/bash
+# Launch V11 Full Parameter Sweep on EPYC Cluster
+
+set -e
+
+echo "================================================================"
+echo "V11 FULL PARAMETER SWEEP - EXHAUSTIVE SEARCH"
+echo "================================================================"
+echo ""
+echo "Grid: 26,244 combinations"
+echo "  - flip_threshold: 0.25, 0.3, 0.35, 0.4, 0.45, 0.5 (6)"
+echo "  - adx_min: 0, 5, 10, 15, 20, 25 (6)"
+echo "  - long_pos_max: 90, 95, 100 (3)"
+echo "  - short_pos_min: 0, 5, 10 (3)"
+echo "  - vol_min: 0.0, 0.5, 1.0 (3)"
+echo "  - entry_buffer_atr: 0.0, 0.05, 0.10 (3)"
+echo "  - rsi_long_min: 20, 25, 30 (3)"
+echo "  - rsi_short_max: 70, 75, 80 (3)"
+echo ""
+echo "Workers:"
+echo "  - worker1: 24 cores (24/7)"
+echo "  - worker2: 18 cores (7PM-6AM only)"
+echo ""
+echo "Estimated Duration: 8-12 hours"
+echo "================================================================"
+echo ""
+
+cd "$(dirname "$0")"
+
+# Check data file
+if [ ! -f "data/solusdt_5m.csv" ]; then
+    echo "✗ Error: data/solusdt_5m.csv not found"
+    exit 1
+fi
+echo "✓ Market data found"
+
+# Check worker script
+if [ ! -f "v11_full_worker.py" ]; then
+    echo "✗ Error: v11_full_worker.py not found"
+    exit 1
+fi
+echo "✓ Worker script found"
+
+# Make scripts executable
+chmod +x v11_full_coordinator.py
+chmod +x v11_full_worker.py
+echo "✓ Scripts executable"
+
+# Create results directory
+mkdir -p v11_results
+echo "✓ Results directory ready"
+
+# Deploy worker to machines
+echo ""
+echo "📦 Deploying worker script to EPYC cluster..."
+
+# Worker 1
+echo "  → worker1 (10.10.254.106)"
+scp v11_full_worker.py root@10.10.254.106:/home/comprehensive_sweep/
+scp ../backtester/v11_moneyline_all_filters.py root@10.10.254.106:/home/comprehensive_sweep/backtester/
+
+# Worker 2 (via worker 1)
+echo "  → worker2 (10.20.254.100) via worker1"
+ssh root@10.10.254.106 "scp /home/comprehensive_sweep/v11_full_worker.py root@10.20.254.100:/home/backtest_dual/backtest/"
+ssh root@10.10.254.106 "scp /home/comprehensive_sweep/backtester/v11_moneyline_all_filters.py root@10.20.254.100:/home/backtest_dual/backtest/backtester/"
+
+echo "✓ Workers deployed"
+
+# Launch coordinator
+echo ""
+echo "🚀 Starting full sweep coordinator..."
+nohup python3 v11_full_coordinator.py > coordinator_v11_full.log 2>&1 &
+COORDINATOR_PID=$!
+
+echo "✓ Coordinator started (PID: $COORDINATOR_PID)"
+echo ""
+echo "================================================================"
+echo "MONITORING"
+echo "================================================================"
+echo "Live log:     tail -f coordinator_v11_full.log"
+echo "Database:     sqlite3 exploration.db"
+echo "Results:      cluster/v11_results/*_results.csv"
+echo ""
+echo "Check status:"
+echo "  sqlite3 exploration.db \\"
+echo "    \"SELECT status, COUNT(*) FROM v11_full_chunks GROUP BY status\""
+echo ""
+echo "Top results so far:"
+echo "  sqlite3 exploration.db \\"
+echo "    \"SELECT params, pnl FROM v11_full_strategies \\"
+echo "     ORDER BY pnl DESC LIMIT 10\""
+echo ""
+echo "To stop sweep:"
+echo "  kill $COORDINATOR_PID"
+echo ""
+echo "Telegram notifications enabled (start/complete/stop)"
+echo "================================================================"

cluster/v11_full_coordinator.py

@@ -0,0 +1,422 @@
+#!/usr/bin/env python3
+"""
+V11 Full Parameter Sweep Coordinator - EXHAUSTIVE SEARCH
+
+Based on test sweep results showing 9.2× improvement over v9.
+Now testing full parameter space to find optimal configuration.
+
+EXHAUSTIVE GRID (16,384 combinations):
+- flip_threshold: 0.25, 0.3, 0.35, 0.4, 0.45, 0.5 (6 values)
+- adx_min: 0, 5, 10, 15, 20, 25 (6 values - 0 = disabled)
+- long_pos_max: 90, 95, 100 (3 values)
+- short_pos_min: 0, 5, 10 (3 values - 0 = disabled)
+- vol_min: 0.0, 0.5, 1.0 (3 values - 0 = disabled)
+- entry_buffer_atr: 0.0, 0.05, 0.10 (3 values - 0 = disabled)
+- rsi_long_min: 20, 25, 30 (3 values)
+- rsi_short_max: 70, 75, 80 (3 values)
+
+Total: 6 * 6 * 3 * 3 * 3 * 3 * 3 * 3 = 26,244 combinations
+Split into ~2,000 combo chunks = 14 chunks
+"""
+
+import sqlite3
+import subprocess
+import time
+import signal
+import sys
+from pathlib import Path
+from datetime import datetime
+import urllib.request
+import urllib.parse
+import json
+import itertools
+
+# Worker configuration
+WORKERS = {
+    'worker1': {
+        'host': 'root@10.10.254.106',
+        'workspace': '/home/comprehensive_sweep',
+        'max_parallel': 24,
+    },
+    'worker2': {
+        'host': 'root@10.20.254.100', 
+        'workspace': '/home/backtest_dual/backtest',
+        'ssh_hop': 'root@10.10.254.106',
+        'max_parallel': 18,
+        'time_restricted': True,
+        'allowed_start_hour': 19,  # 7 PM
+        'allowed_end_hour': 6,     # 6 AM
+    }
+}
+
+DATA_FILE = 'data/solusdt_5m.csv'
+DB_PATH = 'exploration.db'
+CHUNK_SIZE = 2000
+
+# Telegram configuration
+TELEGRAM_BOT_TOKEN = '8240234365:AAEm6hg_XOm54x8ctnwpNYreFKRAEvWU3uY'
+TELEGRAM_CHAT_ID = '579304651'
+
+# EXHAUSTIVE parameter grid
+PARAM_GRID = {
+    'flip_threshold': [0.25, 0.3, 0.35, 0.4, 0.45, 0.5],
+    'adx_min': [0, 5, 10, 15, 20, 25],
+    'long_pos_max': [90, 95, 100],
+    'short_pos_min': [0, 5, 10],
+    'vol_min': [0.0, 0.5, 1.0],
+    'entry_buffer_atr': [0.0, 0.05, 0.10],
+    'rsi_long_min': [20, 25, 30],
+    'rsi_short_max': [70, 75, 80],
+}
+
+def send_telegram_message(message: str):
+    """Send notification to Telegram"""
+    try:
+        url = f"https://api.telegram.org/bot{TELEGRAM_BOT_TOKEN}/sendMessage"
+        data = {
+            'chat_id': TELEGRAM_CHAT_ID,
+            'text': message,
+            'parse_mode': 'HTML'
+        }
+        
+        req = urllib.request.Request(
+            url,
+            data=json.dumps(data).encode('utf-8'),
+            headers={'Content-Type': 'application/json'}
+        )
+        
+        with urllib.request.urlopen(req, timeout=10) as response:
+            if response.status == 200:
+                print(f"✓ Telegram notification sent")
+            else:
+                print(f"⚠️ Telegram notification failed: {response.status}")
+    except Exception as e:
+        print(f"⚠️ Error sending Telegram notification: {e}")
+
+
+def is_worker_allowed_to_run(worker_name: str) -> bool:
+    """Check if worker is allowed to run based on time restrictions"""
+    worker = WORKERS[worker_name]
+    
+    if not worker.get('time_restricted', False):
+        return True
+    
+    current_hour = datetime.now().hour
+    start_hour = worker['allowed_start_hour']
+    end_hour = worker['allowed_end_hour']
+    
+    if start_hour > end_hour:
+        allowed = current_hour >= start_hour or current_hour < end_hour
+    else:
+        allowed = start_hour <= current_hour < end_hour
+    
+    return allowed
+
+
+def signal_handler(sig, frame):
+    """Handle termination signals"""
+    message = (
+        "⚠️ <b>V11 Full Sweep STOPPED</b>\n\n"
+        "Coordinator received termination signal.\n"
+        "Sweep stopped prematurely.\n\n"
+        f"Time: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
+    )
+    send_telegram_message(message)
+    sys.exit(0)
+
+
+def init_db():
+    """Initialize database with v11_full schema"""
+    conn = sqlite3.connect(DB_PATH)
+    c = conn.cursor()
+    
+    # Create chunks table
+    c.execute('''
+        CREATE TABLE IF NOT EXISTS v11_full_chunks (
+            chunk_id TEXT PRIMARY KEY,
+            start_combo INTEGER NOT NULL,
+            end_combo INTEGER NOT NULL,
+            total_combos INTEGER NOT NULL,
+            status TEXT DEFAULT 'pending',
+            assigned_worker TEXT,
+            started_at INTEGER,
+            completed_at INTEGER,
+            best_pnl_in_chunk REAL,
+            results_csv_path TEXT
+        )
+    ''')
+    
+    # Create strategies table for results
+    c.execute('''
+        CREATE TABLE IF NOT EXISTS v11_full_strategies (
+            id INTEGER PRIMARY KEY AUTOINCREMENT,
+            chunk_id TEXT NOT NULL,
+            params TEXT NOT NULL,
+            pnl REAL NOT NULL,
+            win_rate REAL NOT NULL,
+            profit_factor REAL NOT NULL,
+            max_drawdown REAL NOT NULL,
+            total_trades INTEGER NOT NULL,
+            created_at INTEGER DEFAULT (strftime('%s', 'now')),
+            FOREIGN KEY (chunk_id) REFERENCES v11_full_chunks(chunk_id)
+        )
+    ''')
+    
+    c.execute('CREATE INDEX IF NOT EXISTS idx_v11_full_chunk_status ON v11_full_chunks(status)')
+    c.execute('CREATE INDEX IF NOT EXISTS idx_v11_full_strategy_pnl ON v11_full_strategies(pnl DESC)')
+    
+    conn.commit()
+    conn.close()
+    print("✓ Database initialized")
+
+
+def create_chunks():
+    """Create chunks for all parameter combinations"""
+    # Generate all combinations
+    keys = sorted(PARAM_GRID.keys())
+    values = [PARAM_GRID[k] for k in keys]
+    all_combos = list(itertools.product(*values))
+    total_combos = len(all_combos)
+    
+    print(f"Total parameter combinations: {total_combos:,}")
+    
+    conn = sqlite3.connect(DB_PATH)
+    c = conn.cursor()
+    
+    # Check if chunks already exist
+    c.execute('SELECT COUNT(*) FROM v11_full_chunks')
+    existing = c.fetchone()[0]
+    
+    if existing > 0:
+        print(f"⚠️ Found {existing} existing chunks - auto-clearing for fresh sweep")
+        c.execute('DELETE FROM v11_full_chunks')
+        c.execute('DELETE FROM v11_full_strategies')
+        conn.commit()
+        print("✓ Existing chunks deleted")
+    
+    # Create chunks
+    chunk_num = 0
+    for start in range(0, total_combos, CHUNK_SIZE):
+        end = min(start + CHUNK_SIZE, total_combos)
+        chunk_id = f"v11_full_chunk_{chunk_num:04d}"
+        
+        c.execute('''
+            INSERT INTO v11_full_chunks (chunk_id, start_combo, end_combo, total_combos, status)
+            VALUES (?, ?, ?, ?, 'pending')
+        ''', (chunk_id, start, end, end - start))
+        
+        chunk_num += 1
+    
+    conn.commit()
+    conn.close()
+    
+    print(f"✓ Created {chunk_num} chunks ({CHUNK_SIZE} combos each)")
+
+
+def get_next_chunk():
+    """Get next pending chunk"""
+    conn = sqlite3.connect(DB_PATH)
+    c = conn.cursor()
+    
+    c.execute('''
+        SELECT chunk_id, start_combo, end_combo 
+        FROM v11_full_chunks 
+        WHERE status = 'pending'
+        ORDER BY chunk_id
+        LIMIT 1
+    ''')
+    
+    result = c.fetchone()
+    conn.close()
+    
+    return result
+
+
+def get_chunk_stats():
+    """Get current sweep statistics"""
+    conn = sqlite3.connect(DB_PATH)
+    c = conn.cursor()
+    
+    c.execute('''
+        SELECT 
+            SUM(CASE WHEN status = 'pending' THEN 1 ELSE 0 END),
+            SUM(CASE WHEN status = 'running' THEN 1 ELSE 0 END),
+            SUM(CASE WHEN status = 'completed' THEN 1 ELSE 0 END),
+            COUNT(*)
+        FROM v11_full_chunks
+    ''')
+    
+    stats = c.fetchone()
+    conn.close()
+    
+    return {
+        'pending': stats[0] or 0,
+        'running': stats[1] or 0,
+        'completed': stats[2] or 0,
+        'total': stats[3] or 0
+    }
+
+
+def start_worker(worker_name: str, chunk_id: str, start_combo: int, end_combo: int):
+    """Start worker on remote machine"""
+    worker = WORKERS[worker_name]
+    
+    # Mark chunk as running
+    conn = sqlite3.connect(DB_PATH)
+    c = conn.cursor()
+    c.execute('''
+        UPDATE v11_full_chunks 
+        SET status = 'running', assigned_worker = ?, started_at = strftime('%s', 'now')
+        WHERE chunk_id = ?
+    ''', (worker_name, chunk_id))
+    conn.commit()
+    conn.close()
+    
+    # Worker command (use venv python directly)
+    worker_cmd = (
+        f"cd {worker['workspace']} && "
+        f"nohup .venv/bin/python3 v11_full_worker.py "
+        f"--chunk-id {chunk_id} "
+        f"--start {start_combo} "
+        f"--end {end_combo} "
+        f"--workers {worker.get('max_parallel', 24)} "
+        f"> {chunk_id}.log 2>&1 &"
+    )
+    
+    print(f"🚀 Starting {worker_name} on chunk {chunk_id} (combos {start_combo}-{end_combo})")
+    
+    try:
+        # Worker 2 requires SSH through worker 1
+        if worker.get('ssh_hop'):
+            # SSH to worker1, then SSH to worker2 from there
+            hop_cmd = f"ssh {worker['host']} '{worker_cmd}'"
+            full_cmd = ['ssh', worker['ssh_hop'], hop_cmd]
+        else:
+            # Direct SSH to worker1
+            full_cmd = ['ssh', worker['host'], worker_cmd]
+        
+        subprocess.run(full_cmd, check=True, timeout=30)
+        print(f"✓ {worker_name} started successfully")
+        return True
+    except Exception as e:
+        print(f"✗ Failed to start {worker_name}: {e}")
+        # Mark chunk as pending again
+        conn = sqlite3.connect(DB_PATH)
+        c = conn.cursor()
+        c.execute('''
+            UPDATE v11_full_chunks 
+            SET status = 'pending', assigned_worker = NULL, started_at = NULL
+            WHERE chunk_id = ?
+        ''', (chunk_id,))
+        conn.commit()
+        conn.close()
+        return False
+
+
+def main():
+    """Main coordinator loop"""
+    print("=" * 80)
+    print("V11 FULL PARAMETER SWEEP COORDINATOR")
+    print("=" * 80)
+    print()
+    print("Exhaustive Grid: 26,244 combinations")
+    print("Chunk Size: 2,000 combinations")
+    print("Workers: worker1 (24 cores), worker2 (18 cores, 7PM-6AM)")
+    print()
+    
+    # Register signal handlers
+    signal.signal(signal.SIGINT, signal_handler)
+    signal.signal(signal.SIGTERM, signal_handler)
+    
+    # Initialize database
+    init_db()
+    
+    # Create chunks
+    create_chunks()
+    
+    # Get initial stats
+    stats = get_chunk_stats()
+    
+    # Send startup notification
+    message = (
+        f"🚀 <b>V11 Full Sweep STARTED</b>\n\n"
+        f"Total Chunks: {stats['total']}\n"
+        f"Total Combinations: {stats['total'] * CHUNK_SIZE:,}\n"
+        f"Workers: {len(WORKERS)}\n\n"
+        f"Started: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
+    )
+    send_telegram_message(message)
+    
+    print()
+    print("=" * 80)
+    print("SWEEP STARTED")
+    print("=" * 80)
+    print()
+    
+    sweep_start = time.time()
+    
+    try:
+        while True:
+            stats = get_chunk_stats()
+            
+            # Check if sweep complete
+            if stats['pending'] == 0 and stats['running'] == 0:
+                duration = time.time() - sweep_start
+                hours = int(duration // 3600)
+                minutes = int((duration % 3600) // 60)
+                
+                message = (
+                    f"✅ <b>V11 Full Sweep COMPLETE</b>\n\n"
+                    f"Total Chunks: {stats['completed']}\n"
+                    f"Total Combinations: {stats['completed'] * CHUNK_SIZE:,}\n"
+                    f"Duration: {hours}h {minutes}m\n\n"
+                    f"Completed: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
+                )
+                send_telegram_message(message)
+                
+                print()
+                print("=" * 80)
+                print("SWEEP COMPLETE!")
+                print("=" * 80)
+                print(f"Duration: {hours}h {minutes}m")
+                print()
+                break
+            
+            # Assign work to available workers
+            for worker_name in WORKERS.keys():
+                if not is_worker_allowed_to_run(worker_name):
+                    continue
+                
+                # Check if worker already has work
+                conn = sqlite3.connect(DB_PATH)
+                c = conn.cursor()
+                c.execute('''
+                    SELECT COUNT(*) FROM v11_full_chunks 
+                    WHERE status = 'running' AND assigned_worker = ?
+                ''', (worker_name,))
+                running_count = c.fetchone()[0]
+                conn.close()
+                
+                if running_count > 0:
+                    continue
+                
+                # Get next chunk
+                next_chunk = get_next_chunk()
+                if next_chunk:
+                    chunk_id, start_combo, end_combo = next_chunk
+                    start_worker(worker_name, chunk_id, start_combo, end_combo)
+            
+            # Status update
+            print(f"\r[{datetime.now().strftime('%H:%M:%S')}] "
+                  f"Pending: {stats['pending']} | Running: {stats['running']} | "
+                  f"Completed: {stats['completed']}/{stats['total']}", end='', flush=True)
+            
+            time.sleep(30)
+            
+    except KeyboardInterrupt:
+        print("\n\nReceived interrupt signal, cleaning up...")
+        signal_handler(signal.SIGINT, None)
+
+
+if __name__ == '__main__':
+    main()

cluster/v11_full_worker.py

@@ -0,0 +1,175 @@
+#!/usr/bin/env python3
+"""
+V11 Full Sweep Worker - Processes parameter combinations in parallel
+
+Runs on EPYC workers, processes assigned chunk of parameter space.
+"""
+
+import argparse
+import itertools
+import json
+import multiprocessing as mp
+import sys
+import time
+from pathlib import Path
+
+# Add backtester to path
+sys.path.insert(0, str(Path(__file__).parent.parent / 'backtester'))
+
+from backtester.data_loader import load_csv
+from backtester.simulator import run_backtest
+from backtester.v11_moneyline_all_filters import MoneyLineV11Inputs
+
+# Parameter grid (matches coordinator)
+PARAM_GRID = {
+    'flip_threshold': [0.25, 0.3, 0.35, 0.4, 0.45, 0.5],
+    'adx_min': [0, 5, 10, 15, 20, 25],
+    'long_pos_max': [90, 95, 100],
+    'short_pos_min': [0, 5, 10],
+    'vol_min': [0.0, 0.5, 1.0],
+    'entry_buffer_atr': [0.0, 0.05, 0.10],
+    'rsi_long_min': [20, 25, 30],
+    'rsi_short_max': [70, 75, 80],
+}
+
+
+def test_single_config(args):
+    """Test a single parameter configuration"""
+    combo_idx, params_tuple, data = args
+    
+    # Unpack parameters
+    keys = sorted(PARAM_GRID.keys())
+    params = dict(zip(keys, params_tuple))
+    
+    # Create inputs
+    inputs = MoneyLineV11Inputs(
+        flip_threshold=params['flip_threshold'],
+        adx_min=params['adx_min'],
+        long_pos_max=params['long_pos_max'],
+        short_pos_min=params['short_pos_min'],
+        vol_min=params['vol_min'],
+        entry_buffer_atr=params['entry_buffer_atr'],
+        rsi_long_min=params['rsi_long_min'],
+        rsi_short_max=params['rsi_short_max'],
+    )
+    
+    try:
+        # Run backtest
+        results = run_backtest(data, inputs, 'v11')
+        
+        return {
+            'params': params,
+            'pnl': results['total_pnl'],
+            'win_rate': results['win_rate'],
+            'profit_factor': results['profit_factor'],
+            'max_drawdown': results['max_drawdown'],
+            'total_trades': results['total_trades'],
+        }
+    except Exception as e:
+        print(f"Error testing combo {combo_idx}: {e}")
+        return None
+
+
+def main():
+    parser = argparse.ArgumentParser(description='V11 Full Sweep Worker')
+    parser.add_argument('--chunk-id', required=True, help='Chunk ID')
+    parser.add_argument('--start', type=int, required=True, help='Start combo index')
+    parser.add_argument('--end', type=int, required=True, help='End combo index')
+    parser.add_argument('--workers', type=int, default=24, help='Parallel workers')
+    args = parser.parse_args()
+    
+    print(f"V11 Full Worker: {args.chunk_id}")
+    print(f"Range: {args.start} - {args.end}")
+    print(f"Workers: {args.workers}")
+    print()
+    
+    # Load data
+    print("Loading market data...")
+    data = load_csv(Path('data/solusdt_5m.csv'), 'SOLUSDT', '5m')
+    print(f"Loaded {len(data)} candles")
+    print()
+    
+    # Generate all combinations
+    keys = sorted(PARAM_GRID.keys())
+    values = [PARAM_GRID[k] for k in keys]
+    all_combos = list(itertools.product(*values))
+    
+    # Get this chunk's combos
+    chunk_combos = all_combos[args.start:args.end]
+    print(f"Testing {len(chunk_combos)} combinations...")
+    print()
+    
+    # Prepare args for parallel processing
+    test_args = [
+        (args.start + i, combo, data) 
+        for i, combo in enumerate(chunk_combos)
+    ]
+    
+    # Run tests in parallel
+    start_time = time.time()
+    results = []
+    
+    with mp.Pool(processes=args.workers) as pool:
+        for i, result in enumerate(pool.imap_unordered(test_single_config, test_args)):
+            if result:
+                results.append(result)
+            
+            # Progress update every 10 combos
+            if (i + 1) % 10 == 0:
+                elapsed = time.time() - start_time
+                rate = (i + 1) / elapsed
+                remaining = len(chunk_combos) - (i + 1)
+                eta = remaining / rate if rate > 0 else 0
+                
+                print(f"Progress: {i+1}/{len(chunk_combos)} "
+                      f"({rate:.1f} combos/s, ETA: {eta/60:.1f}m)")
+    
+    # Sort by P&L descending
+    results.sort(key=lambda x: x['pnl'], reverse=True)
+    
+    # Save results to CSV
+    output_path = Path(f"v11_results/{args.chunk_id}_results.csv")
+    output_path.parent.mkdir(exist_ok=True)
+    
+    with open(output_path, 'w') as f:
+        # Header
+        param_cols = sorted(PARAM_GRID.keys())
+        metric_cols = ['pnl', 'win_rate', 'profit_factor', 'max_drawdown', 'total_trades']
+        header = ','.join(param_cols + metric_cols)
+        f.write(header + '\n')
+        
+        # Data rows
+        for result in results:
+            param_values = [str(result['params'][k]) for k in param_cols]
+            metric_values = [
+                f"{result['pnl']:.1f}",
+                f"{result['win_rate']:.1f}",
+                f"{result['profit_factor']:.3f}",
+                f"{result['max_drawdown']:.1f}",
+                str(result['total_trades'])
+            ]
+            row = ','.join(param_values + metric_values)
+            f.write(row + '\n')
+    
+    duration = time.time() - start_time
+    print()
+    print("=" * 60)
+    print(f"Chunk {args.chunk_id} COMPLETE")
+    print(f"Duration: {duration/60:.1f} minutes")
+    print(f"Rate: {len(chunk_combos)/duration:.2f} combos/second")
+    print(f"Results saved: {output_path}")
+    
+    if results:
+        best = results[0]
+        print()
+        print("Best configuration in chunk:")
+        print(f"  P&L: ${best['pnl']:.2f}")
+        print(f"  Win Rate: {best['win_rate']:.1f}%")
+        print(f"  Profit Factor: {best['profit_factor']:.3f}")
+        print(f"  Parameters: {best['params']}")
+    
+    print("=" * 60)
+
+
+if __name__ == '__main__':
+    main()

cluster/v11_full_worker_FIXED.py

@@ -0,0 +1,311 @@
+#!/usr/bin/env python3
+"""
+V11 Full Parameter Sweep Worker
+
+Processes chunks of v11 parameter configurations (26,244 combinations total).
+Uses all available cores for multiprocessing.
+
+FULL EXHAUSTIVE SWEEP across all filter parameters.
+"""
+
+import sys
+import csv
+import pandas as pd
+from pathlib import Path
+from typing import Dict, List, Any
+from multiprocessing import Pool
+import functools
+import itertools
+
+# Add current directory to path for v11_moneyline_all_filters import
+sys.path.insert(0, str(Path(__file__).parent))
+
+from v11_moneyline_all_filters import (
+    money_line_v11_signals, 
+    MoneyLineV11Inputs
+)
+from backtester.simulator import simulate_money_line
+
+# CPU limit: Use all available cores (24 for worker1, 18 for worker2)
+MAX_WORKERS = 24  # Default, overridden by --workers argument
+
+# Global data file path (set by init_worker)
+_DATA_FILE = None
+
+def init_worker(data_file):
+    """Initialize worker process with data file path"""
+    global _DATA_FILE
+    _DATA_FILE = data_file
+
+# FULL EXHAUSTIVE Parameter grid (26,244 combinations)
+PARAMETER_GRID = {
+    'flip_threshold': [0.25, 0.3, 0.35, 0.4, 0.45, 0.5],  # 6 values
+    'adx_min': [0, 5, 10, 15, 20, 25],                     # 6 values
+    'long_pos_max': [90, 95, 100],                         # 3 values
+    'short_pos_min': [0, 5, 10],                           # 3 values
+    'vol_min': [0.0, 0.5, 1.0],                            # 3 values
+    'entry_buffer_atr': [0.0, 0.05, 0.10],                 # 3 values
+    'rsi_long_min': [20, 25, 30],                          # 3 values
+    'rsi_short_max': [70, 75, 80],                         # 3 values
+}
+# Total: 6×6×3×3×3×3×3×3 = 26,244 combos
+
+
+def load_market_data(csv_file: str) -> pd.DataFrame:
+    """Load OHLCV data from CSV"""
+    df = pd.read_csv(csv_file)
+    
+    # Ensure required columns exist
+    required = ['timestamp', 'open', 'high', 'low', 'close', 'volume']
+    for col in required:
+        if col not in df.columns:
+            raise ValueError(f"Missing required column: {col}")
+    
+    # Convert timestamp if needed
+    if df['timestamp'].dtype == 'object':
+        df['timestamp'] = pd.to_datetime(df['timestamp'])
+    
+    df = df.set_index('timestamp')
+    print(f"✓ Loaded {len(df):,} bars from {csv_file}")
+    return df
+
+
+def backtest_config(config: Dict[str, Any]) -> Dict[str, Any]:
+    """
+    Run backtest for single v11 test parameter configuration
+    
+    Loads data from global _DATA_FILE path on first call.
+    
+    Returns dict with:
+        - params: original config dict
+        - pnl: total P&L
+        - trades: number of trades
+        - win_rate: % winners
+        - profit_factor: wins/losses ratio
+        - max_drawdown: max drawdown $
+    """
+    # Load data (cached per worker process)
+    global _DATA_FILE
+    df = pd.read_csv(_DATA_FILE)
+    df['timestamp'] = pd.to_datetime(df['timestamp'])
+    df = df.set_index('timestamp')
+    
+    try:
+        # Create v11 inputs
+        inputs = MoneyLineV11Inputs(
+            use_quality_filters=True,  # 🔧 FIX: Enable filters for progressive sweep
+            flip_threshold=config['flip_threshold'],
+            adx_min=config['adx_min'],
+            long_pos_max=config['long_pos_max'],
+            short_pos_min=config['short_pos_min'],
+            vol_min=config['vol_min'],
+            entry_buffer_atr=config['entry_buffer_atr'],
+            rsi_long_min=config['rsi_long_min'],
+            rsi_long_max=70,  # 🔧 FIX: Add missing fixed parameter
+            rsi_short_min=30,  # 🔧 FIX: Add missing fixed parameter
+            rsi_short_max=config['rsi_short_max'],
+        )
+        
+        print(f"  Generating signals...", flush=True)
+        # Generate signals
+        signals = money_line_v11_signals(df, inputs)
+        print(f"  Got {len(signals)} signals, simulating...", flush=True)
+        
+        if not signals:
+            return {
+                'params': config,
+                'pnl': 0.0,
+                'trades': 0,
+                'win_rate': 0.0,
+                'profit_factor': 0.0,
+                'max_drawdown': 0.0,
+            }
+        
+        # Simple backtesting: track equity curve
+        equity = 1000.0  # Starting capital
+        peak_equity = equity
+        max_drawdown = 0.0
+        wins = 0
+        losses = 0
+        win_pnl = 0.0
+        loss_pnl = 0.0
+        
+        for signal in signals:
+            # Simple trade simulation
+            # TP1 at +0.86%, SL at -1.29% (ATR-based defaults)
+            entry = signal.entry_price
+            
+            # Look ahead in data to see if TP or SL hit
+            signal_idx = df.index.get_loc(signal.timestamp)
+            
+            # Look ahead up to 100 bars
+            max_bars = min(100, len(df) - signal_idx - 1)
+            if max_bars <= 0:
+                continue
+                
+            future_data = df.iloc[signal_idx+1:signal_idx+1+max_bars]
+            
+            if signal.direction == "long":
+                tp_price = entry * 1.0086  # +0.86%
+                sl_price = entry * 0.9871  # -1.29%
+                
+                # Check if TP or SL hit
+                hit_tp = (future_data['high'] >= tp_price).any()
+                hit_sl = (future_data['low'] <= sl_price).any()
+                
+                if hit_tp:
+                    pnl = 1000.0 * 0.0086  # $8.60 on $1000 position
+                    equity += pnl
+                    wins += 1
+                    win_pnl += pnl
+                elif hit_sl:
+                    pnl = -1000.0 * 0.0129  # -$12.90 on $1000 position
+                    equity += pnl
+                    losses += 1
+                    loss_pnl += abs(pnl)
+            else:  # short
+                tp_price = entry * 0.9914  # -0.86%
+                sl_price = entry * 1.0129  # +1.29%
+                
+                # Check if TP or SL hit
+                hit_tp = (future_data['low'] <= tp_price).any()
+                hit_sl = (future_data['high'] >= sl_price).any()
+                
+                if hit_tp:
+                    pnl = 1000.0 * 0.0086  # $8.60 on $1000 position
+                    equity += pnl
+                    wins += 1
+                    win_pnl += pnl
+                elif hit_sl:
+                    pnl = -1000.0 * 0.0129  # -$12.90 on $1000 position
+                    equity += pnl
+                    losses += 1
+                    loss_pnl += abs(pnl)
+            
+            # Track drawdown
+            peak_equity = max(peak_equity, equity)
+            current_drawdown = peak_equity - equity
+            max_drawdown = max(max_drawdown, current_drawdown)
+        
+        total_trades = wins + losses
+        win_rate = wins / total_trades if total_trades > 0 else 0.0
+        profit_factor = win_pnl / loss_pnl if loss_pnl > 0 else (float('inf') if win_pnl > 0 else 0.0)
+        total_pnl = equity - 1000.0
+        
+        return {
+            'params': config,
+            'pnl': round(total_pnl, 2),
+            'trades': total_trades,
+            'win_rate': round(win_rate * 100, 1),
+            'profit_factor': round(profit_factor, 3) if profit_factor != float('inf') else 999.0,
+            'max_drawdown': round(max_drawdown, 2),
+        }
+        
+    except Exception as e:
+        print(f"✗ Error backtesting config: {e}")
+        return {
+            'params': config,
+            'pnl': 0.0,
+            'trades': 0,
+            'win_rate': 0.0,
+            'profit_factor': 0.0,
+            'max_drawdown': 0.0,
+        }
+
+
+def generate_parameter_combinations() -> List[Dict[str, Any]]:
+    """Generate all 256 parameter combinations"""
+    keys = PARAMETER_GRID.keys()
+    values = PARAMETER_GRID.values()
+    
+    combinations = []
+    for combo in itertools.product(*values):
+        config = dict(zip(keys, combo))
+        combinations.append(config)
+    
+    return combinations
+
+
+def process_chunk(data_file: str, chunk_id: str, start_idx: int, end_idx: int):
+    """Process a chunk of parameter combinations"""
+    print(f"\n{'='*60}")
+    print(f"V11 Test Worker - {chunk_id}")
+    print(f"Processing combinations {start_idx} to {end_idx-1}")
+    print(f"{'='*60}\n")
+    
+    # Load market data
+    df = load_market_data(data_file)
+    
+    # Generate all combinations
+    all_combos = generate_parameter_combinations()
+    print(f"✓ Generated {len(all_combos)} total combinations")
+    
+    # Get this chunk's combinations
+    chunk_combos = all_combos[start_idx:end_idx]
+    print(f"✓ Processing {len(chunk_combos)} combinations in this chunk\n")
+    
+    # Backtest with multiprocessing (pass data file path instead of dataframe)
+    print(f"⚡ Starting {MAX_WORKERS}-core backtest...\n")
+    
+    with Pool(processes=MAX_WORKERS, initializer=init_worker, initargs=(data_file,)) as pool:
+        results = pool.map(backtest_config, chunk_combos)
+    
+    print(f"\n✓ Completed {len(results)} backtests")
+    
+    # Write results to CSV
+    output_dir = Path('v11_test_results')
+    output_dir.mkdir(exist_ok=True)
+    
+    csv_file = output_dir / f"{chunk_id}_results.csv"
+    
+    with open(csv_file, 'w', newline='') as f:
+        writer = csv.writer(f)
+        
+        # Header
+        writer.writerow([
+            'flip_threshold', 'adx_min', 'long_pos_max', 'short_pos_min',
+            'vol_min', 'entry_buffer_atr', 'rsi_long_min', 'rsi_short_max',
+            'pnl', 'win_rate', 'profit_factor', 'max_drawdown', 'total_trades'
+        ])
+        
+        # Data rows
+        for result in results:
+            params = result['params']
+            writer.writerow([
+                params['flip_threshold'],
+                params['adx_min'],
+                params['long_pos_max'],
+                params['short_pos_min'],
+                params['vol_min'],
+                params['entry_buffer_atr'],
+                params['rsi_long_min'],
+                params['rsi_short_max'],
+                result['pnl'],
+                result['win_rate'],
+                result['profit_factor'],
+                result['max_drawdown'],
+                result['trades'],
+            ])
+    
+    print(f"✓ Results saved to {csv_file}")
+    
+    # Show top 5 results
+    sorted_results = sorted(results, key=lambda x: x['pnl'], reverse=True)
+    print(f"\n🏆 Top 5 Results:")
+    for i, r in enumerate(sorted_results[:5], 1):
+        print(f"  {i}. PnL: ${r['pnl']:,.2f} | Trades: {r['trades']} | WR: {r['win_rate']}%")
+
+
+if __name__ == '__main__':
+    if len(sys.argv) != 4:
+        print("Usage: python v11_test_worker.py <data_file> <chunk_id> <start_idx>")
+        sys.exit(1)
+    
+    data_file = sys.argv[1]
+    chunk_id = sys.argv[2]
+    start_idx = int(sys.argv[3])
+    
+    # Calculate end index (256 combos per chunk)
+    end_idx = start_idx + 256
+    
+    process_chunk(data_file, chunk_id, start_idx, end_idx)

workflows/trading/parse_signal_enhanced.json.backup

@@ -3,7 +3,7 @@
   "nodes": [
     {
       "parameters": {
-        "jsCode": "// Get the body - it might be a string or nested in an object\nlet body = $json.body || $json.query?.body || JSON.stringify($json);\n\n// If body is an object, stringify it\nif (typeof body === 'object') {\n  body = JSON.stringify(body);\n}\n\n// Parse basic signal (existing logic)\nconst symbolMatch = body.match(/\\b(SOL|BTC|ETH)\\b/i);\nconst symbol = symbolMatch ? symbolMatch[1].toUpperCase() + '-PERP' : 'SOL-PERP';\n\nconst direction = body.match(/\\b(sell|short)\\b/i) ? 'short' : 'long';\n\n// Enhanced timeframe extraction supporting multiple formats:\n// - \"buy 5\" → \"5\"\n// - \"buy 15\" → \"15\"\n// - \"buy 60\" or \"buy 1h\" → \"60\"\n// - \"buy 240\" or \"buy 4h\" → \"240\"\n// - \"buy D\" or \"buy 1d\" → \"D\"\n// - \"buy W\" → \"W\"\nconst timeframeMatch = body.match(/\\b(buy|sell)\\s+(\\d+|D|W|M|1h|4h|1d)\\b/i);\nlet timeframe = '5'; // Default to 5min\n\nif (timeframeMatch) {\n  const tf = timeframeMatch[2];\n  // Convert hour/day notation to minutes\n  if (tf === '1h' || tf === '60') {\n    timeframe = '60';\n  } else if (tf === '4h' || tf === '240') {\n    timeframe = '240';\n  } else if (tf === '1d' || tf.toUpperCase() === 'D') {\n    timeframe = 'D';\n  } else if (tf.toUpperCase() === 'W') {\n    timeframe = 'W';\n  } else if (tf.toUpperCase() === 'M') {\n    timeframe = 'M';\n  } else {\n    timeframe = tf;\n  }\n}\n\n// Parse new context metrics from enhanced format:\n// \"SOLT.P buy 15 | ATR:0.65 | ADX:14.3 | RSI:51.3 | VOL:0.87 | POS:59.3 | MAGAP:-1.23 | IND:v9\"\nconst atrMatch = body.match(/ATR:([\\d.]+)/);\nconst atr = atrMatch ? parseFloat(atrMatch[1]) : 0;\n\nconst adxMatch = body.match(/ADX:([\\d.]+)/);\nconst adx = adxMatch ? parseFloat(adxMatch[1]) : 0;\n\nconst rsiMatch = body.match(/RSI:([\\d.]+)/);\nconst rsi = rsiMatch ? parseFloat(rsiMatch[1]) : 0;\n\nconst volumeMatch = body.match(/VOL:([\\d.]+)/);\nconst volumeRatio = volumeMatch ? parseFloat(volumeMatch[1]) : 0;\n\nconst pricePositionMatch = body.match(/POS:([\\d.]+)/);\nconst pricePosition = pricePositionMatch ? parseFloat(pricePositionMatch[1]) : 0;\n\n// Parse signal price from \"@ price\" format (for 1min data feed and v9 signals)\n// Must match: \"buy 1 @ 142.08 |\" (@ followed by price before first pipe)\n// DEBUG: Log body to see actual format\nconsole.log('DEBUG body:', body);\nconst signalPriceMatch = body.match(/@\\s*([\\d.]+)\\s*\\|/);\nconsole.log('DEBUG signalPriceMatch:', signalPriceMatch);\nconst signalPrice = signalPriceMatch ? parseFloat(signalPriceMatch[1]) : undefined;\nconsole.log('DEBUG signalPrice:', signalPrice, 'pricePosition will be:', body.match(/POS:([\\d.]+)/) ? body.match(/POS:([\\d.]+)/)[1] : 'not found');\n\n// V9: Parse MA gap (optional, backward compatible with v8)\nconst maGapMatch = body.match(/MAGAP:([-\\d.]+)/);\nconst maGap = maGapMatch ? parseFloat(maGapMatch[1]) : undefined;\n\n// Parse indicator version (optional, backward compatible)\nconst indicatorVersionMatch = body.match(/IND:(v\\d+)/i);\nconst indicatorVersion = indicatorVersionMatch ? indicatorVersionMatch[1] : 'v5';\n\nreturn {\n  rawMessage: body,\n  symbol,\n  direction,\n  timeframe,\n  signalPrice, // NEW: Actual price from TradingView\n  // Context fields\n  atr,\n  adx,\n  rsi,\n  volumeRatio,\n  pricePosition,\n  maGap, // V9 NEW\n  // Version tracking (defaults to v5 for backward compatibility)\n  indicatorVersion\n};"
+        "jsCode": "// Get the body - it might be a string or nested in an object\nlet body = $json.body || $json.query?.body || JSON.stringify($json);\n\n// If body is an object, stringify it\nif (typeof body === 'object') {\n  body = JSON.stringify(body);\n}\n\n// Detect MA crossover events (death cross / golden cross)\nconst isMACrossover = body.match(/crossing/i) !== null;\n\n// Parse basic signal (existing logic)\nconst symbolMatch = body.match(/\\b(SOL|BTC|ETH)\\b/i);\nconst symbol = symbolMatch ? symbolMatch[1].toUpperCase() + '-PERP' : 'SOL-PERP';\n\nconst direction = body.match(/\\b(sell|short)\\b/i) ? 'short' : 'long';\n\n// Determine crossover type based on direction\nconst isDeathCross = isMACrossover && direction === 'short';\nconst isGoldenCross = isMACrossover && direction === 'long';\n\n// Enhanced timeframe extraction supporting multiple formats:\n// - \"buy 5\" → \"5\"\n// - \"buy 15\" → \"15\"\n// - \"buy 60\" or \"buy 1h\" → \"60\"\n// - \"buy 240\" or \"buy 4h\" → \"240\"\n// - \"buy D\" or \"buy 1d\" → \"D\"\n// - \"buy W\" → \"W\"\nconst timeframeMatch = body.match(/\\b(buy|sell)\\s+(\\d+|D|W|M|1h|4h|1d)\\b/i);\nlet timeframe = '5'; // Default to 5min\n\nif (timeframeMatch) {\n  const tf = timeframeMatch[2];\n  // Convert hour/day notation to minutes\n  if (tf === '1h' || tf === '60') {\n    timeframe = '60';\n  } else if (tf === '4h' || tf === '240') {\n    timeframe = '240';\n  } else if (tf === '1d' || tf.toUpperCase() === 'D') {\n    timeframe = 'D';\n  } else if (tf.toUpperCase() === 'W') {\n    timeframe = 'W';\n  } else if (tf.toUpperCase() === 'M') {\n    timeframe = 'M';\n  } else {\n    timeframe = tf;\n  }\n}\n\n// Parse new context metrics from enhanced format:\n// \"SOLT.P buy 15 | ATR:0.65 | ADX:14.3 | RSI:51.3 | VOL:0.87 | POS:59.3 | MAGAP:-1.23 | IND:v9\"\nconst atrMatch = body.match(/ATR:([\\d.]+)/);\nconst atr = atrMatch ? parseFloat(atrMatch[1]) : 0;\n\nconst adxMatch = body.match(/ADX:([\\d.]+)/);\nconst adx = adxMatch ? parseFloat(adxMatch[1]) : 0;\n\nconst rsiMatch = body.match(/RSI:([\\d.]+)/);\nconst rsi = rsiMatch ? parseFloat(rsiMatch[1]) : 0;\n\nconst volumeMatch = body.match(/VOL:([\\d.]+)/);\nconst volumeRatio = volumeMatch ? parseFloat(volumeMatch[1]) : 0;\n\nconst pricePositionMatch = body.match(/POS:([\\d.]+)/);\nconst pricePosition = pricePositionMatch ? parseFloat(pricePositionMatch[1]) : 0;\n\n// Parse signal price from \"@ price\" format (for 1min data feed and v9 signals)\n// Must match: \"buy 1 @ 142.08 |\" (@ followed by price before first pipe)\n// DEBUG: Log body to see actual format\nconsole.log('DEBUG body:', body);\nconst signalPriceMatch = body.match(/@\\s*([\\d.]+)\\s*\\|/);\nconsole.log('DEBUG signalPriceMatch:', signalPriceMatch);\nconst signalPrice = signalPriceMatch ? parseFloat(signalPriceMatch[1]) : undefined;\nconsole.log('DEBUG signalPrice:', signalPrice, 'pricePosition will be:', body.match(/POS:([\\d.]+)/) ? body.match(/POS:([\\d.]+)/)[1] : 'not found');\n\n// V9: Parse MA gap (optional, backward compatible with v8)\nconst maGapMatch = body.match(/MAGAP:([-\\d.]+)/);\nconst maGap = maGapMatch ? parseFloat(maGapMatch[1]) : undefined;\n\n// Parse indicator version (optional, backward compatible)\nconst indicatorVersionMatch = body.match(/IND:(v\\d+)/i);\nconst indicatorVersion = indicatorVersionMatch ? indicatorVersionMatch[1] : 'v5';\n\nreturn {\n  rawMessage: body,\n  symbol,\n  direction,\n  timeframe,\n  signalPrice,\n  // Context fields\n  atr,\n  adx,\n  rsi,\n  volumeRatio,\n  pricePosition,\n  maGap,\n  // MA Crossover detection (NEW: Nov 27, 2025)\n  isMACrossover,\n  isDeathCross,\n  isGoldenCross,\n  // Version tracking\n  indicatorVersion\n};"
       },
       "id": "parse-signal-enhanced",
       "name": "Parse Signal Enhanced",
@@ -19,6 +19,6 @@
   "staticData": null,
   "tags": [],
   "triggerCount": 0,
-  "updatedAt": "2025-10-30T00:00:00.000Z",
+  "updatedAt": "2025-11-27T00:00:00.000Z",
-  "versionId": "1"
+  "versionId": "2"
 }