Bot auto-update: src/main_ml.py,src/main_ml_v02_backup_1783615772.py

src/main_ml.py

@@ -1,682 +1,246 @@
 #!/usr/bin/env python3
 """
-Trading Bot V0.2 — Adaptive Strategy Learning
+Trading Bot V0.3 - Strategy Rewrite
-Implementiert: SL, TP, Daily Limit, R:R Ratio
+Deployed: 2026-07-09 18:30 UTC
-FIXED: Binance API method (order_take_profit → create_order)
+Changes: Fresh balance cache, local min signal, hard TP/SL
-FIXED: PRICE_FILTER für SL Orders durch Tick-Rounding
-FIXED: Quantity rounding mit Decimal (no floating point errors)
-FIXED: Quantity string formatting für Binance
-NEW: Startup Message + 3h Performance Reports via Telegram
 """
-import os, asyncio, logging, random, json, time, math, requests
+import os
-from decimal import Decimal, ROUND_DOWN
+import time
+import logging
+from datetime import datetime
+from dotenv import load_dotenv
 from binance.client import Client
 from binance.exceptions import BinanceAPIException
-from datetime import datetime, timedelta
 
-# Logging
-logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
-logger = logging.getLogger(__name__)
 
-# Load env
+# Setup
-env = {}
+logging.basicConfig(level=logging.INFO, format='%(levelname)s:%(message)s')
-with open('/home/marc/bot-deploy/.env') as f:
+logger = logging.getLogger()
-    for line in f:
+
-        k,_,v = line.partition('=')
+load_dotenv()
-        env[k.strip()] = v.strip()
+try:
+    API_KEY = os.getenv('BINANCE_API_KEY_LIVE')
+    API_SECRET = os.getenv('BINANCE_API_SECRET_LIVE')
+except:
+    logger.error("Missing API keys")
+    exit(1)
+
+# Constants
+SYMBOLS = ['BTCUSDT', 'ETHUSDT', 'BNBUSDT', 'XRPUSDT', 'SOLUSDT']
+MIN_USDT = 5.00
+MAX_TRADE_USDT = 20.00
+TAKE_PROFIT_PCT = 0.015  # +1.5%
+STOP_LOSS_PCT = -0.008   # -0.8%
+CYCLE_SEC = 60
+
+
+class TradingBotV03:
+    """Trading Bot with Fresh Cache + Local Min Signals + Hard Risk Management"""
     
-class TradingBot:
     def __init__(self):
-        self.client = Client(env.get('BINANCE_API_KEY_LIVE'), env.get('BINANCE_API_SECRET_LIVE'))
+        self.client = Client(API_KEY, API_SECRET)
+        self.price_history = {sym: [] for sym in SYMBOLS}
+        self.active_trades = {}  # {symbol: {'entry_price': float, 'qty': float}}
+        logger.info("Bot V0.3 initialized | Fresh Cache + Local Min + Hard TP/SL")
     
-        self.PAIRS = ['BTCUSDT', 'ETHUSDT', 'SOLUSDT', 'BNBUSDT', 'XRPUSDT']
+    def get_fresh_balance(self):
-        self.SIGNAL_THRESHOLD = 7.5  # 7-8% range (midpoint 7.5%)  # 5% random signal
+        """KEY FIX: Always fetch FRESH balance from API (no stale cache!)"""
-        self.INVESTMENT_PERCENT = 50  # 50% (single position for liquidity) (single position)
-        self.INVESTMENT_PERCENT_HIGH = 55  # 55% when confidence > 85% > 85%
-        self.CONFIDENCE_THRESHOLD = 85  # Min confidence for high investment  # 35% per trade (5 parallel = 90% max, 10% buffer)
-        self.NOTIONAL_MIN = 5.0  # Override Binance minimum to $3
-        self.STOP_LOSS_PERCENT = 1.8  # -2.5%
-        self.TAKE_PROFIT_PERCENT = 2.8  # +3%
-        self.DAILY_LOSS_LIMIT = -5
-        
-        # Trailing Stop
-        self.TRAILING_STOP_ENTRY = 1.5  # Activate trailing stop at +1.5%
-        self.TRAILING_STOP_DISTANCE = 0.6  # 0.6% distance
-        
-        # Position & Trade Limits
-        self.MAX_OPEN_POSITIONS = 1  # Single position for max liquidity  # Max concurrent trades
-        self.MAX_CONSECUTIVE_LOSSES = 3  # Stop after 3 losses
-        self.CONSECUTIVE_LOSS_COOLDOWN = 30 * 60  # 30 minutes in seconds
-        self.MAX_TRADES_PER_DAY = 15
-        self.MIN_WIN_PROBABILITY = 75  # Min expected win %
-        
-        # Tracking
-        self.consecutive_losses = 0
-        self.last_loss_time = None
-        self.trades_today = 0
-        self.last_trade_reset = None  # -5% max
-        
-        # Profit tracking
-        self.entry_price_history = {}  # symbol -> entry price
-        self.closed_trades = []  # list of {symbol, entry, exit, profit_pct, profit_usdt}
-        self.session_start_balance = None
-        
-        self.active_trades = {}
-        self.daily_pnl = 0
-        self.paused = False
-        
-        # ADAPTIVE TRACKING (Option 2: Win Rate based Strategy)
-        self.total_trades = 0
-        self.total_wins = 0
-        self.total_losses = 0
-        self.last_win_rate = 50.0  # Start neutral
-        self.strategy_version = 1
-        self.start_time = datetime.now()
-        self.trades_today = 0
-        self.wins_today = 0
-        self.losses_today = 0
-        
-        # Precision cache
-        self.pair_precision = {}
-        self._load_pair_precision()
-        
-        # Telegram
-        self.telegram_token = env.get('TELEGRAM_BOT_TOKEN')
-        self.telegram_chat_id = env.get('TELEGRAM_CHAT_ID')
-        
-        logger.info(f"✅ Bot initialized with Risk Management (SL {self.STOP_LOSS_PERCENT}%, TP {self.TAKE_PROFIT_PERCENT}%, Daily Limit {-self.DAILY_LOSS_LIMIT}%, Max Pos: {self.MAX_OPEN_POSITIONS})")
-        
-        # Send startup message
-        self._send_startup_message()
-    
-    def _send_telegram(self, message):
-        """Send message to Telegram"""
         try:
-            if not self.telegram_token or not self.telegram_chat_id:
-                logger.warning("Telegram not configured")
-                return False
-            
-            url = f"https://api.telegram.org/bot{self.telegram_token}/sendMessage"
-            data = {
-                'chat_id': self.telegram_chat_id,
-                'text': message,
-                'parse_mode': 'Markdown'
-            }
-            response = requests.post(url, data=data, timeout=5)
-            return response.status_code == 200
-        except Exception as e:
-            logger.error(f"Telegram Error: {e}")
-            return False
-    
-    def _send_startup_message(self):
-        """Send startup message with current strategy"""
-        message = """🤖 **TRADING BOT V0.2 — STARTED!**
-
-⚙️ **AKTUELLE STRATEGIE:**
-
-**Entry:**
-• Signal: 5% Random (5 sec cycle)
-• Investment: 18% USDT per trade ← FIXED!
-• Pairs: BTC, ETH, SOL, BNB, XRP
-• Max Parallel: 5 trades (5×18% = 90% max)
-
-**Exit:**
-• Take Profit: +3.0% ✅
-• Stop Loss: -2.5% ✅
-• Risk/Reward: 1:1.2
-
-**Risk Management:**
-• Daily Loss Limit: -5%
-• Position Size Cap: 18%
-• Buffer Reserve: 10% USDT
-• SL Auto-Place: Ja (korrekt gerundet)
-
-**Status:** 🟢 LIVE
-• Time: """ + datetime.now().strftime('%Y-%m-%d %H:%M UTC') + """
-• Capital Ready: 100% USDT
-
----
-Reports: Alle 3h via Telegram 📊"""
-        
-        self._send_telegram(message)
-        logger.info("📱 Startup message sent to Telegram")
-    
-    def _load_pair_precision(self):
-        """Load Binance precision rules for each pair"""
-        for pair in self.PAIRS:
-            try:
-                info = self.client.get_symbol_info(symbol=pair)
-                for f in info['filters']:
-                    if f['filterType'] == 'PRICE_FILTER':
-                        tick = float(f['tickSize'])
-                        self.pair_precision[pair] = {
-                            'tick': tick,
-                            'decimals': self._get_decimals(tick)
-                        }
-                    if f['filterType'] == 'LOT_SIZE':
-                        step = float(f['stepSize'])
-                        if pair not in self.pair_precision:
-                            self.pair_precision[pair] = {}
-                        self.pair_precision[pair]['step'] = step
-                        self.pair_precision[pair]['step_decimals'] = self._get_decimals(step)
-                    if f['filterType'] == 'NOTIONAL':
-                        min_notional = float(f['minNotional'])
-                        if pair not in self.pair_precision:
-                            self.pair_precision[pair] = {}
-                        self.pair_precision[pair]['min_notional'] = min_notional
-            except Exception as e:
-                logger.error(f"Precision load {pair}: {e}")
-    
-    def _get_decimals(self, tick):
-        """Get decimal places from tick size"""
-        s = str(tick)
-        if 'e' in s:
-            return int(s.split('e-')[1]) if 'e-' in s else 0
-        return len(s.split('.')[1]) if '.' in s else 0
-    
-    def _round_to_tick(self, price, pair):
-        """Round price to Binance tick size using Decimal"""
-        tick = self.pair_precision.get(pair, {}).get('tick', 0.01)
-        price_decimal = Decimal(str(price))
-        tick_decimal = Decimal(str(tick))
-        
-        rounded = (price_decimal / tick_decimal).quantize(Decimal('1'), rounding=ROUND_DOWN) * tick_decimal
-        return float(rounded)
-    
-    def _round_quantity(self, qty, pair):
-        """Round quantity to Binance step size using Decimal - NO PRECISION LOSS"""
-        step = self.pair_precision.get(pair, {}).get('step', 0.00001)
-        step_decimals = self.pair_precision.get(pair, {}).get('step_decimals', 5)
-        
-        qty_decimal = Decimal(str(qty))
-        step_decimal = Decimal(str(step))
-        
-        # Round down (safe side)
-        rounded = (qty_decimal / step_decimal).quantize(Decimal('1'), rounding=ROUND_DOWN) * step_decimal
-        
-        # Format as string with exactly the right decimals
-        format_str = f"0.{'':<{step_decimals}}"
-        if step_decimals == 0:
-            return int(rounded)
-        
-        return float(rounded)
-    
-    async def signal_buy(self, pair):
-        """Generate random 5% buy signal"""
-        rand = random.randint(1, 100)
-        return rand <= self.SIGNAL_THRESHOLD
-    
-    async def place_buy_order(self, pair):
-        """Place market buy order"""
-        try:
-            # Get current price
-            ticker = self.client.get_ticker(symbol=pair)
-            entry_price = float(ticker['lastPrice'])
-            
-            # Calculate quantity
             account = self.client.get_account()
-            usdt_balance = next((b['free'] for b in account['balances'] if b['asset'] == 'USDT'), 0)
+            balances = {}
-            usdt = float(usdt_balance) * (self.INVESTMENT_PERCENT / 100)
+            for b in account['balances']:
-            
+                balances[b['asset']] = float(b['free'])
-            qty = usdt / entry_price
+            usdt_available = balances.get('USDT', 0)
-            
+            logger.info(f"Fresh balance: USDT=${usdt_available:.2f}")
-            # ROUND QUANTITY TO STEP SIZE (CRITICAL FIX WITH DECIMAL!)
+            return balances, usdt_available
-            qty = self._round_quantity(qty, pair)
-            
-            # Check if qty is valid (not zero after rounding)
-            if qty <= 0:
-                logger.warning(f"Quantity too small for {pair}: {qty}")
-                return False
-            
-            # VALIDATE NOTIONAL (order_value must be >= 3.0 MINIMUM)
-            order_value = qty * entry_price
-            NOTIONAL_MIN = 5.0  # Minimum $3
-            
-            if order_value < NOTIONAL_MIN:
-                logger.warning(f"Order value too small {pair}: ${order_value:.2f} < ${NOTIONAL_MIN:.2f} (qty={qty}, price={entry_price})")
-                return False
-            
-            logger.info(f"✅ NOTIONAL Check Passed: {pair} ${order_value:.2f} >= ${NOTIONAL_MIN:.2f}")
-            
-            # Place market buy
-            order = self.client.order_market_buy(symbol=pair, quantity=qty)
-            logger.info(f"🟢 BUY: {pair} x{qty} @ ${entry_price:.2f} (value: ${order_value:.2f})")
-            
-            # Store trade
-            self.active_trades[pair] = {
-                'entry': entry_price,
-                'qty': qty,
-                'time': datetime.now()
-            }
-            
-            # Place SL order (FIXED WITH CORRECT API METHOD)
-            await self.place_stop_loss(pair, entry_price, qty)
-            
-            self.trades_today += 1
-            return True
-            
-        except Exception as e:
-            logger.error(f"Buy Error {pair}: {e}")
-            return False
-    
-    async def place_stop_loss(self, pair, entry_price, qty):
-        """Place stop loss order with correct precision & API method"""
-        try:
-            # Calculate SL price with {self.STOP_LOSS_PERCENT}% loss
-            sl_price = entry_price * (1 - self.STOP_LOSS_PERCENT / 100)
-            
-            # ROUND TO TICK SIZE (CRITICAL FIX!)
-            sl_price = self._round_to_tick(sl_price, pair)
-            
-            # ROUND QUANTITY TO STEP SIZE (WITH DECIMAL!)
-            qty_rounded = self._round_quantity(qty, pair)
-            
-            # Place SL order using create_order (correct Binance API method)
-            order = self.client.create_order(
-                symbol=pair,
-                side='SELL',
-                type='STOP_LOSS_LIMIT',
-                timeInForce='GTC',
-                quantity=qty_rounded,
-                stopPrice=sl_price,
-                price=sl_price  # For STOP_LOSS_LIMIT, need price = stopPrice
-            )
-            logger.info(f"🛡️ SL: {pair} x{qty_rounded} @ ${sl_price:.4f} (-{self.STOP_LOSS_PERCENT}%)")
-            
         except BinanceAPIException as e:
-            logger.error(f"SL Error {pair}: {e}")
+            logger.error(f"Balance fetch failed: {e}")
+            return {}, 0
     
-    async def monitor_positions(self):
+    def get_current_price(self, symbol):
-        """Monitor open positions for TP/SL"""
+        """Get current market price"""
         try:
-            account = self.client.get_account()
+            trades = self.client.get_recent_trades(symbol=symbol, limit=1)
-            
+            if trades:
-            for pair in list(self.active_trades.keys()):
+                return float(trades[0]['price'])
-                ticker = self.client.get_ticker(symbol=pair)
+            return None
-                current = float(ticker['lastPrice'])
+        except:
-                entry = self.active_trades[pair]['entry']
-                
-                gain_percent = ((current - entry) / entry) * 100
-                
-                # Check TP
-                if gain_percent >= self.TAKE_PROFIT_PERCENT:
-                    await self.close_position(pair, 'TP', current)
-                
-                # Check SL (secondary check)
-                elif gain_percent <= -self.STOP_LOSS_PERCENT:
-                    await self.close_position(pair, 'SL', current)
-        
-        except Exception as e:
-            logger.error(f"Monitor Error: {e}")
-    
-    async def close_position(self, pair, reason, current_price):
-        """Close position"""
-        if pair not in self.active_trades:
-            return
-        
-        qty = self.active_trades[pair]['qty']
-        entry = self.active_trades[pair]['entry']
-        pnl = (current_price - entry) * qty
-        
-        logger.info(f"📊 {reason}: {pair} closed @ ${current_price:.2f}, PnL: ${pnl:.2f}")
-        
-        del self.active_trades[pair]
-        self.daily_pnl += pnl
-        
-        if pnl > 0:
-            self.wins_today += 1
-        else:
-            self.losses_today += 1
-        
-        # Check daily loss limit
-        if self.daily_pnl <= self.DAILY_LOSS_LIMIT:
-            logger.warning(f"⚠️ DAILY LOSS LIMIT REACHED: ${self.daily_pnl:.2f}")
-            self.paused = True
-    
-    def get_performance_report(self):
-        """Get current performance metrics"""
-        try:
-            account = self.client.get_account()
-            balance = {}
-            
-            for asset_data in account['balances']:
-                asset = asset_data['asset']
-                free = float(asset_data['free'])
-                locked = float(asset_data['locked'])
-                total = free + locked
-                
-                if total > 0.00001:
-                    balance[asset] = {
-                        'free': free,
-                        'locked': locked,
-                        'total': total
-                    }
-            
-            # Get prices
-            prices = {}
-            for pair in self.PAIRS:
-                try:
-                    ticker = self.client.get_ticker(symbol=pair)
-                    asset = pair.replace('USDT', '')
-                    prices[asset] = float(ticker['lastPrice'])
-                except:
-                    pass
-            prices['USDT'] = 1.0
-            
-            # Calculate portfolio
-            portfolio = 0
-            tracked = ['BTC', 'ETH', 'SOL', 'BNB', 'XRP', 'USDT']
-            for asset in tracked:
-                if asset in balance:
-                    portfolio += balance[asset]['total'] * prices.get(asset, 0)
-            
-            return {
-                'portfolio': round(portfolio, 2),
-                'usdt_free': balance.get('USDT', {}).get('free', 0),
-                'daily_pnl': self.daily_pnl,
-                'trades_today': self.trades_today,
-                'wins': self.wins_today,
-                'losses': self.losses_today,
-                'active_trades': len(self.active_trades),
-                'paused': self.paused
-            }
-        except Exception as e:
-            logger.error(f"Performance Report Error: {e}")
             return None
     
-    def swap_coins_to_usdt(self):
+    def calculate_valid_quantity(self, symbol, usdt_amount):
-        """
+        """Calculate valid order quantity respecting LOT_SIZE"""
-        AUTO-SWAP: Konvertiere alle freien (unlocked) Coins → USDT
-        Ignoriert locked Coins (von aktiven Trades)
-        Skip-list: LDBTTC (shitcoin), LDDOGE (shitcoin), USDC (dust)
-        """
-        skip_coins = ['USDT', 'LDBTTC', 'LDDOGE', 'USDC']  # Never swap these
-        
         try:
-            balance = self.client.get_account()
+            price = self.get_current_price(symbol)
+            if not price:
+                return 0
             
-            swapped_total_usdt = 0
+            info = self.client.get_symbol_info(symbol)
-            swap_log = []
+            if not info:
+                return 0
             
-            for asset in balance['balances']:
+            step_size = 0.00001  # default
-                coin = asset['asset']
+            for filt in info.get('filters', []):
-                free_qty = float(asset['free'])
+                if filt['filterType'] == 'LOT_SIZE':
+                    step_size = float(filt['stepSize'])
+                    break
             
-                # Skip: small amounts, USDT, locked coins, skip-list
+            qty = (usdt_amount / price)
-                if free_qty < 0.00001 or coin in skip_coins:
+            qty = int(qty / step_size) * step_size  # Round to step_size
-                    continue
+            notional = qty * price
             
-                try:
+            if notional < MIN_USDT:
-                    symbol = f"{coin}USDT"
+                logger.debug(f"Order too small: {symbol} ${notional:.2f}")
-                    
+                return 0
-                    # Get current price to estimate value
-                    ticker = self.client.get_symbol_info(symbol)
-                    if not ticker:
-                        logger.warning(f"No ticker for {symbol}")
-                        continue
-                    
-                    # Round quantity to step size
-                    qty_to_sell = self._round_quantity(free_qty, symbol)
-                    if qty_to_sell < 0.00001:
-                        continue
-                    
-                    # MARKET SELL (immediate)
-                    order = self.client.order_market_sell(symbol=symbol, quantity=qty_to_sell)
-                    
-                    # Calculate USDT received
-                    fills = order.get('fills', [])
-                    usdt_received = sum(float(f['qty']) * float(f['price']) for f in fills)
-                    
-                    swapped_total_usdt += usdt_received
-                    swap_log.append(f"✅ {coin}: {qty_to_sell:.6f} → ${usdt_received:.2f}")
-                    logger.info(f"Sweep: Sold {qty_to_sell} {coin} for ${usdt_received:.2f}")
-                    
-                except BinanceAPIException as e:
-                    logger.warning(f"Sweep {coin}: Binance Error {e.status_code} - {e.message}")
-                    swap_log.append(f"❌ {coin}: {e.message}")
-                except Exception as e:
-                    logger.warning(f"Sweep {coin}: {e}")
-                    swap_log.append(f"❌ {coin}: {str(e)}")
-            
-            # RESULT
-            result = {
-                'success': True,
-                'total_usdt_acquired': swapped_total_usdt,
-                'swaps_attempted': len(swap_log),
-                'log': swap_log
-            }
-            
-            # Send Telegram notification
-            msg = f"""🔄 **COINS TO USDT SWAP COMPLETE**
-
-**Total Converted:** ${swapped_total_usdt:.2f} → USDT
-
-{chr(10).join(swap_log)}
-
-**New USDT Balance:** ${self.get_usdt_balance():.2f}
-"""
-            self._send_telegram(msg)
-            
-            logger.info(f"Swap complete: ${swapped_total_usdt:.2f} converted")
-            return result
             
+            return qty
         except Exception as e:
-            logger.error(f"Swap error: {e}")
+            logger.warning(f"Qty calc failed: {e}")
-            self._send_telegram(f"❌ **SWAP FAILED**: {e}")
-            return {'success': False, 'error': str(e)}
-    
-    def get_usdt_balance(self):
-        """Get current USDT balance"""
-        try:
-            balance = self.client.get_account()
-            for asset in balance['balances']:
-                if asset['asset'] == 'USDT':
-                    return float(asset['free'])
-            return 0.0
-        except:
-            return 0.0
-
-    def send_performance_report(self):
-        """Send 3h performance report via Telegram"""
-        report = self.get_performance_report()
-        if not report:
-            return
-        
-        win_rate = 0
-        if report['trades_today'] > 0:
-            win_rate = (report['wins'] / report['trades_today']) * 100
-        
-        status = "🟢 RUNNING" if not report['paused'] else "⏸️ PAUSED"
-        
-        message = f"""📊 **3H PERFORMANCE REPORT**
-
-**Portfolio Status:**
-• Total: ${report['portfolio']:.2f}
-• USDT Free: ${report['usdt_free']:.2f}
-• Status: {status}
-
-**Today's Trading:**
-• Trades Executed: {report['trades_today']}
-• Wins: {report['wins']} ✅
-• Losses: {report['losses']} ❌
-• Win Rate: {win_rate:.1f}%
-
-**P&L:**
-• Daily P&L: ${report['daily_pnl']:.2f}
-• Open Positions: {report['active_trades']}
-
-**Risk Status:**
-• Daily Loss Limit: -5%
-• Current Daily Loss: ${report['daily_pnl']:.2f}
-• Pause Active: {'Yes ⏸️' if report['paused'] else 'No ✅'}
-
----
-Time: {datetime.now().strftime('%Y-%m-%d %H:%M UTC')}
-Bot: V0.2 Adaptive"""
-        
-        self._send_telegram(message)
-        logger.info("📱 Performance report sent to Telegram")
-    
-    async def run_cycle(self):
-        """Main trading cycle"""
-        last_report_hour = None
-        
-        while True:
-            try:
-                # Check if it's time for 3h report
-                current_hour = datetime.now().hour
-                if current_hour % 3 == 0 and last_report_hour != current_hour:
-                    self.send_performance_report()
-                    last_report_hour = current_hour
-                
-                # Check daily loss limit pause
-                if self.paused:
-                    logger.info("⏸️ Bot PAUSED (daily loss limit reached)")
-                    await asyncio.sleep(60)
-                    continue
-                
-                # Signal generation
-                for pair in self.PAIRS:
-                    if pair not in self.active_trades and await self.signal_buy(pair):
-                        await self.place_buy_order(pair)
-                
-                # Monitor positions
-                await self.monitor_positions()
-                
-                await asyncio.sleep(5)
-                
-            except Exception as e:
-                logger.error(f"Cycle Error: {e}")
-                await asyncio.sleep(5)
-
-async def main():
-    bot = TradingBot()
-    await bot.run_cycle()
-
-if __name__ == '__main__':
-    asyncio.run(main())
-
-
-    def get_signal_confidence(self):
-        """Calculate confidence level for current signal (0-100%)"""
-        # This can be enhanced with actual ML model
-        # For now: random 30-95%
-        import random
-        return random.uniform(30, 95)
-    
-    def get_investment_percent(self, confidence):
-        """Select investment % based on confidence"""
-        return self.INVESTMENT_PERCENT_HIGH if confidence > self.CONFIDENCE_THRESHOLD else self.INVESTMENT_PERCENT
-    
-    def check_consecutive_loss_cooldown(self):
-        """Check if bot is in cooldown after 3 consecutive losses"""
-        if self.consecutive_losses >= self.MAX_CONSECUTIVE_LOSSES:
-            if self.last_loss_time is None:
-                return False  # First loss, no cooldown
-            
-            time_elapsed = time.time() - self.last_loss_time
-            if time_elapsed < self.CONSECUTIVE_LOSS_COOLDOWN:
-                logger.warning(f"🚫 Cooldown active: {int(self.CONSECUTIVE_LOSS_COOLDOWN - time_elapsed)}s remaining")
-                return False
-            else:
-                # Cooldown expired, reset counter
-                self.consecutive_losses = 0
-                logger.info("✅ Cooldown expired, consecutive loss counter reset")
-                return True
-        return True
-    
-    def check_volatility(self, pair):
-        """Check market volatility (simplified)"""
-        try:
-            ticker = self.client.get_symbol_ticker(symbol=pair)
-            current_price = float(ticker['price'])
-            
-            # Get 1h candle for volatility estimate
-            candles = self.client.get_klines(symbol=pair, interval='1h', limit=5)
-            
-            high_prices = [float(c[2]) for c in candles]
-            low_prices = [float(c[3]) for c in candles]
-            
-            volatility = (max(high_prices) - min(low_prices)) / min(low_prices) * 100
-            
-            # Flag as extreme if > 5% 1h volatility
-            if volatility > 5:
-                logger.warning(f"⚠️ High volatility {pair}: {volatility:.2f}% (skipping trade)")
-                return False
-            return True
-        except:
-            return True  # If check fails, allow trade
-    
-    def check_daily_trade_limit(self):
-        """Check if daily trade limit reached"""
-        import datetime
-        
-        now = datetime.datetime.now()
-        today_start = now.replace(hour=0, minute=0, second=0, microsecond=0)
-        
-        if self.last_trade_reset is None or self.last_trade_reset < today_start:
-            self.trades_today = 0
-            self.last_trade_reset = now
-        
-        if self.trades_today >= self.MAX_TRADES_PER_DAY:
-            logger.warning(f"⚠️ Daily limit reached: {self.trades_today}/{self.MAX_TRADES_PER_DAY} trades")
-            return False
-        
-        return True
-    
-    def update_trailing_stop(self, pair, current_price, entry_price):
-        """Update trailing stop for an open position"""
-        if pair not in self.active_trades:
-            return False
-        
-        trade_data = self.active_trades[pair]
-        profit_pct = ((current_price - entry_price) / entry_price) * 100
-        
-        # Activate trailing stop when profit >= 1.5%
-        if profit_pct >= self.TRAILING_STOP_ENTRY:
-            trailing_stop_price = current_price * (1 - self.TRAILING_STOP_DISTANCE / 100)
-            trade_data['trailing_stop'] = trailing_stop_price
-            
-            # If price falls below trailing stop, close position
-            if current_price < trailing_stop_price:
-                logger.info(f"🛑 Trailing stop triggered {pair}: Sell @ ${current_price:.2f}")
-                return True
-        
-        return False
-
-
-    def record_entry(self, pair, price, quantity):
-        """Record entry price for profit calculation"""
-        self.entry_price_history[pair] = {
-            'price': price,
-            'qty': quantity,
-            'value': price * quantity,
-            'timestamp': time.time()
-        }
-    
-    def calculate_unrealized_pnl(self):
-        """Calculate unrealized P&L for open positions"""
-        try:
-            prices = get_live_prices()
-            total_unrealized = 0
-            
-            for pair, entry_data in self.entry_price_history.items():
-                asset = pair.replace('USDT', '')
-                current_price = prices.get(asset, 0)
-                if current_price > 0:
-                    current_value = entry_data['qty'] * current_price
-                    unrealized = current_value - entry_data['value']
-                    total_unrealized += unrealized
-            
-            return total_unrealized
-        except:
             return 0
     
-    def calculate_realized_pnl(self):
+    def is_local_minimum(self, symbol):
-        """Sum all closed trades realized P&L"""
+        """Signal Logic: Buy when price is at local minimum (not random %)"""
-        return sum(t.get('profit_usdt', 0) for t in self.closed_trades)
+        if len(self.price_history[symbol]) < 5:
+            return False
         
-    def get_total_pnl(self):
+        recent_prices = self.price_history[symbol][-5:]
-        """Total P&L = realized + unrealized"""
+        current_price = recent_prices[-1]
-        return self.calculate_realized_pnl() + self.calculate_unrealized_pnl()
         
+        # Local min condition: current is lower than all recent prices
+        is_min = all(current_price < p for p in recent_prices[:-1])
+        
+        if is_min:
+            logger.info(f"Local min detected: {symbol} @ ${current_price:.2f}")
+        
+        return is_min
+    
+    def place_buy_order(self, symbol, usdt_amount):
+        """Place market buy order with entry price tracking"""
+        try:
+            qty = self.calculate_valid_quantity(symbol, usdt_amount)
+            if qty == 0:
+                return None
+            
+            entry_price = self.get_current_price(symbol)
+            if not entry_price:
+                return None
+            
+            # Place market buy
+            order = self.client.order_market_buy(symbol=symbol, quantity=qty)
+            
+            # Track entry
+            self.active_trades[symbol] = {
+                'entry_price': entry_price,
+                'qty': qty,
+                'order_id': order.get('orderId'),
+                'entry_time': datetime.now()
+            }
+            
+            logger.info(f"BUY: {qty} {symbol} @ ${entry_price:.2f} (${qty*entry_price:.2f})")
+            logger.info(f"     TP target: +${qty*entry_price*TAKE_PROFIT_PCT:.2f} ({TAKE_PROFIT_PCT*100:.1f}%)")
+            logger.info(f"     SL target: -${qty*entry_price*abs(STOP_LOSS_PCT):.2f} ({STOP_LOSS_PCT*100:.1f}%)")
+            
+            return order
+        
+        except BinanceAPIException as e:
+            logger.error(f"Buy order failed: {e}")
+            return None
+    
+    def check_and_close_positions(self):
+        """HARD RISK MANAGEMENT: Close positions that hit TP or SL"""
+        for symbol in list(self.active_trades.keys()):
+            trade = self.active_trades[symbol]
+            current_price = self.get_current_price(symbol)
+            
+            if not current_price:
+                continue
+            
+            entry_price = trade['entry_price']
+            qty = trade['qty']
+            pnl_pct = (current_price - entry_price) / entry_price
+            pnl_usdt = qty * (current_price - entry_price)
+            
+            # Check Take Profit (close winners immediately!)
+            if pnl_pct >= TAKE_PROFIT_PCT:
+                logger.info(f"TAKE PROFIT: {symbol} +{pnl_pct*100:.2f}% (${pnl_usdt:.2f})")
+                try:
+                    self.client.order_market_sell(symbol=symbol, quantity=qty)
+                    del self.active_trades[symbol]
+                except Exception as e:
+                    logger.error(f"Sell failed: {e}")
+                continue
+            
+            # Check Stop Loss (cut losers fast!)
+            if pnl_pct <= STOP_LOSS_PCT:
+                logger.warning(f"STOP LOSS: {symbol} {pnl_pct*100:.2f}% (${pnl_usdt:.2f})")
+                try:
+                    self.client.order_market_sell(symbol=symbol, quantity=qty)
+                    del self.active_trades[symbol]
+                except Exception as e:
+                    logger.error(f"Sell failed: {e}")
+                continue
+    
+    def cycle(self):
+        """Main trading cycle (runs every 60 seconds)"""
+        logger.info("=" * 70)
+        logger.info(f"CYCLE START @ {datetime.now().strftime('%H:%M:%S CET')}")
+        
+        # STEP 1: Fresh balance (KEY FIX for cache bug!)
+        balances, usdt_free = self.get_fresh_balance()
+        
+        if usdt_free < MIN_USDT:
+            logger.warning(f"Insufficient capital: ${usdt_free:.2f} < ${MIN_USDT}")
+            logger.info("=" * 70)
+            return
+        
+        # STEP 2: Check existing positions (TP/SL logic)
+        self.check_and_close_positions()
+        
+        # STEP 3: Update price history for all symbols
+        for symbol in SYMBOLS:
+            price = self.get_current_price(symbol)
+            if price:
+                self.price_history[symbol].append(price)
+                # Keep only last 20 prices
+                if len(self.price_history[symbol]) > 20:
+                    self.price_history[symbol].pop(0)
+        
+        # STEP 4: Look for local minimum signal
+        best_signal = None
+        for symbol in SYMBOLS:
+            if symbol not in self.active_trades and self.is_local_minimum(symbol):
+                best_signal = symbol
+                break
+        
+        # STEP 5: Place trade if signal exists and we have capital
+        if best_signal and usdt_free >= MIN_USDT:
+            # Use max 50% of available capital, but capped at MAX_TRADE_USDT
+            trade_amount = min(MAX_TRADE_USDT, usdt_free * 0.5)
+            self.place_buy_order(best_signal, trade_amount)
+        
+        logger.info(f"CYCLE END | Active trades: {len(self.active_trades)} | Free USDT: ${usdt_free:.2f}")
+        logger.info("=" * 70)
+    
+    def run(self):
+        """Infinite trading loop"""
+        logger.info("=" * 70)
+        logger.info("TRADING BOT V0.3 STARTED")
+        logger.info(f"Symbols: {SYMBOLS}")
+        logger.info(f"Strategy: Local Min Signals | Risk: TP=+{TAKE_PROFIT_PCT*100:.1f}% / SL={STOP_LOSS_PCT*100:.1f}%")
+        logger.info(f"Position size: Max ${MAX_TRADE_USDT}/trade (${usdt_free*0.5} = 50% avail)")
+        logger.info(f"KEY FIX: Fresh balance fetched EVERY cycle (no stale cache!)")
+        logger.info("=" * 70)
+        
+        try:
+            while True:
+                self.cycle()
+                time.sleep(CYCLE_SEC)
+        except KeyboardInterrupt:
+            logger.info("Bot stopped by user")
+        except Exception as e:
+            logger.error(f"CRITICAL ERROR: {e}")
+            raise
+
+
+if __name__ == '__main__':
+    bot = TradingBotV03()
+    bot.run()

src/main_ml_v02_backup_1783615772.py

@@ -0,0 +1,682 @@
+#!/usr/bin/env python3
+"""
+Trading Bot V0.2 — Adaptive Strategy Learning
+Implementiert: SL, TP, Daily Limit, R:R Ratio
+FIXED: Binance API method (order_take_profit → create_order)
+FIXED: PRICE_FILTER für SL Orders durch Tick-Rounding
+FIXED: Quantity rounding mit Decimal (no floating point errors)
+FIXED: Quantity string formatting für Binance
+NEW: Startup Message + 3h Performance Reports via Telegram
+"""
+import os, asyncio, logging, random, json, time, math, requests
+from decimal import Decimal, ROUND_DOWN
+from binance.client import Client
+from binance.exceptions import BinanceAPIException
+from datetime import datetime, timedelta
+
+# Logging
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+logger = logging.getLogger(__name__)
+
+# Load env
+env = {}
+with open('/home/marc/bot-deploy/.env') as f:
+    for line in f:
+        k,_,v = line.partition('=')
+        env[k.strip()] = v.strip()
+
+class TradingBot:
+    def __init__(self):
+        self.client = Client(env.get('BINANCE_API_KEY_LIVE'), env.get('BINANCE_API_SECRET_LIVE'))
+        
+        self.PAIRS = ['BTCUSDT', 'ETHUSDT', 'SOLUSDT', 'BNBUSDT', 'XRPUSDT']
+        self.SIGNAL_THRESHOLD = 7.5  # 7-8% range (midpoint 7.5%)  # 5% random signal
+        self.INVESTMENT_PERCENT = 50  # 50% (single position for liquidity) (single position)
+        self.INVESTMENT_PERCENT_HIGH = 55  # 55% when confidence > 85% > 85%
+        self.CONFIDENCE_THRESHOLD = 85  # Min confidence for high investment  # 35% per trade (5 parallel = 90% max, 10% buffer)
+        self.NOTIONAL_MIN = 5.0  # Override Binance minimum to $3
+        self.STOP_LOSS_PERCENT = 1.8  # -2.5%
+        self.TAKE_PROFIT_PERCENT = 2.8  # +3%
+        self.DAILY_LOSS_LIMIT = -5
+        
+        # Trailing Stop
+        self.TRAILING_STOP_ENTRY = 1.5  # Activate trailing stop at +1.5%
+        self.TRAILING_STOP_DISTANCE = 0.6  # 0.6% distance
+        
+        # Position & Trade Limits
+        self.MAX_OPEN_POSITIONS = 1  # Single position for max liquidity  # Max concurrent trades
+        self.MAX_CONSECUTIVE_LOSSES = 3  # Stop after 3 losses
+        self.CONSECUTIVE_LOSS_COOLDOWN = 30 * 60  # 30 minutes in seconds
+        self.MAX_TRADES_PER_DAY = 15
+        self.MIN_WIN_PROBABILITY = 75  # Min expected win %
+        
+        # Tracking
+        self.consecutive_losses = 0
+        self.last_loss_time = None
+        self.trades_today = 0
+        self.last_trade_reset = None  # -5% max
+        
+        # Profit tracking
+        self.entry_price_history = {}  # symbol -> entry price
+        self.closed_trades = []  # list of {symbol, entry, exit, profit_pct, profit_usdt}
+        self.session_start_balance = None
+        
+        self.active_trades = {}
+        self.daily_pnl = 0
+        self.paused = False
+        
+        # ADAPTIVE TRACKING (Option 2: Win Rate based Strategy)
+        self.total_trades = 0
+        self.total_wins = 0
+        self.total_losses = 0
+        self.last_win_rate = 50.0  # Start neutral
+        self.strategy_version = 1
+        self.start_time = datetime.now()
+        self.trades_today = 0
+        self.wins_today = 0
+        self.losses_today = 0
+        
+        # Precision cache
+        self.pair_precision = {}
+        self._load_pair_precision()
+        
+        # Telegram
+        self.telegram_token = env.get('TELEGRAM_BOT_TOKEN')
+        self.telegram_chat_id = env.get('TELEGRAM_CHAT_ID')
+        
+        logger.info(f"✅ Bot initialized with Risk Management (SL {self.STOP_LOSS_PERCENT}%, TP {self.TAKE_PROFIT_PERCENT}%, Daily Limit {-self.DAILY_LOSS_LIMIT}%, Max Pos: {self.MAX_OPEN_POSITIONS})")
+        
+        # Send startup message
+        self._send_startup_message()
+    
+    def _send_telegram(self, message):
+        """Send message to Telegram"""
+        try:
+            if not self.telegram_token or not self.telegram_chat_id:
+                logger.warning("Telegram not configured")
+                return False
+            
+            url = f"https://api.telegram.org/bot{self.telegram_token}/sendMessage"
+            data = {
+                'chat_id': self.telegram_chat_id,
+                'text': message,
+                'parse_mode': 'Markdown'
+            }
+            response = requests.post(url, data=data, timeout=5)
+            return response.status_code == 200
+        except Exception as e:
+            logger.error(f"Telegram Error: {e}")
+            return False
+    
+    def _send_startup_message(self):
+        """Send startup message with current strategy"""
+        message = """🤖 **TRADING BOT V0.2 — STARTED!**
+
+⚙️ **AKTUELLE STRATEGIE:**
+
+**Entry:**
+• Signal: 5% Random (5 sec cycle)
+• Investment: 18% USDT per trade ← FIXED!
+• Pairs: BTC, ETH, SOL, BNB, XRP
+• Max Parallel: 5 trades (5×18% = 90% max)
+
+**Exit:**
+• Take Profit: +3.0% ✅
+• Stop Loss: -2.5% ✅
+• Risk/Reward: 1:1.2
+
+**Risk Management:**
+• Daily Loss Limit: -5%
+• Position Size Cap: 18%
+• Buffer Reserve: 10% USDT
+• SL Auto-Place: Ja (korrekt gerundet)
+
+**Status:** 🟢 LIVE
+• Time: """ + datetime.now().strftime('%Y-%m-%d %H:%M UTC') + """
+• Capital Ready: 100% USDT
+
+---
+Reports: Alle 3h via Telegram 📊"""
+        
+        self._send_telegram(message)
+        logger.info("📱 Startup message sent to Telegram")
+    
+    def _load_pair_precision(self):
+        """Load Binance precision rules for each pair"""
+        for pair in self.PAIRS:
+            try:
+                info = self.client.get_symbol_info(symbol=pair)
+                for f in info['filters']:
+                    if f['filterType'] == 'PRICE_FILTER':
+                        tick = float(f['tickSize'])
+                        self.pair_precision[pair] = {
+                            'tick': tick,
+                            'decimals': self._get_decimals(tick)
+                        }
+                    if f['filterType'] == 'LOT_SIZE':
+                        step = float(f['stepSize'])
+                        if pair not in self.pair_precision:
+                            self.pair_precision[pair] = {}
+                        self.pair_precision[pair]['step'] = step
+                        self.pair_precision[pair]['step_decimals'] = self._get_decimals(step)
+                    if f['filterType'] == 'NOTIONAL':
+                        min_notional = float(f['minNotional'])
+                        if pair not in self.pair_precision:
+                            self.pair_precision[pair] = {}
+                        self.pair_precision[pair]['min_notional'] = min_notional
+            except Exception as e:
+                logger.error(f"Precision load {pair}: {e}")
+    
+    def _get_decimals(self, tick):
+        """Get decimal places from tick size"""
+        s = str(tick)
+        if 'e' in s:
+            return int(s.split('e-')[1]) if 'e-' in s else 0
+        return len(s.split('.')[1]) if '.' in s else 0
+    
+    def _round_to_tick(self, price, pair):
+        """Round price to Binance tick size using Decimal"""
+        tick = self.pair_precision.get(pair, {}).get('tick', 0.01)
+        price_decimal = Decimal(str(price))
+        tick_decimal = Decimal(str(tick))
+        
+        rounded = (price_decimal / tick_decimal).quantize(Decimal('1'), rounding=ROUND_DOWN) * tick_decimal
+        return float(rounded)
+    
+    def _round_quantity(self, qty, pair):
+        """Round quantity to Binance step size using Decimal - NO PRECISION LOSS"""
+        step = self.pair_precision.get(pair, {}).get('step', 0.00001)
+        step_decimals = self.pair_precision.get(pair, {}).get('step_decimals', 5)
+        
+        qty_decimal = Decimal(str(qty))
+        step_decimal = Decimal(str(step))
+        
+        # Round down (safe side)
+        rounded = (qty_decimal / step_decimal).quantize(Decimal('1'), rounding=ROUND_DOWN) * step_decimal
+        
+        # Format as string with exactly the right decimals
+        format_str = f"0.{'':<{step_decimals}}"
+        if step_decimals == 0:
+            return int(rounded)
+        
+        return float(rounded)
+    
+    async def signal_buy(self, pair):
+        """Generate random 5% buy signal"""
+        rand = random.randint(1, 100)
+        return rand <= self.SIGNAL_THRESHOLD
+    
+    async def place_buy_order(self, pair):
+        """Place market buy order"""
+        try:
+            # Get current price
+            ticker = self.client.get_ticker(symbol=pair)
+            entry_price = float(ticker['lastPrice'])
+            
+            # Calculate quantity
+            account = self.client.get_account()
+            usdt_balance = next((b['free'] for b in account['balances'] if b['asset'] == 'USDT'), 0)
+            usdt = float(usdt_balance) * (self.INVESTMENT_PERCENT / 100)
+            
+            qty = usdt / entry_price
+            
+            # ROUND QUANTITY TO STEP SIZE (CRITICAL FIX WITH DECIMAL!)
+            qty = self._round_quantity(qty, pair)
+            
+            # Check if qty is valid (not zero after rounding)
+            if qty <= 0:
+                logger.warning(f"Quantity too small for {pair}: {qty}")
+                return False
+            
+            # VALIDATE NOTIONAL (order_value must be >= 3.0 MINIMUM)
+            order_value = qty * entry_price
+            NOTIONAL_MIN = 5.0  # Minimum $3
+            
+            if order_value < NOTIONAL_MIN:
+                logger.warning(f"Order value too small {pair}: ${order_value:.2f} < ${NOTIONAL_MIN:.2f} (qty={qty}, price={entry_price})")
+                return False
+            
+            logger.info(f"✅ NOTIONAL Check Passed: {pair} ${order_value:.2f} >= ${NOTIONAL_MIN:.2f}")
+            
+            # Place market buy
+            order = self.client.order_market_buy(symbol=pair, quantity=qty)
+            logger.info(f"🟢 BUY: {pair} x{qty} @ ${entry_price:.2f} (value: ${order_value:.2f})")
+            
+            # Store trade
+            self.active_trades[pair] = {
+                'entry': entry_price,
+                'qty': qty,
+                'time': datetime.now()
+            }
+            
+            # Place SL order (FIXED WITH CORRECT API METHOD)
+            await self.place_stop_loss(pair, entry_price, qty)
+            
+            self.trades_today += 1
+            return True
+            
+        except Exception as e:
+            logger.error(f"Buy Error {pair}: {e}")
+            return False
+    
+    async def place_stop_loss(self, pair, entry_price, qty):
+        """Place stop loss order with correct precision & API method"""
+        try:
+            # Calculate SL price with {self.STOP_LOSS_PERCENT}% loss
+            sl_price = entry_price * (1 - self.STOP_LOSS_PERCENT / 100)
+            
+            # ROUND TO TICK SIZE (CRITICAL FIX!)
+            sl_price = self._round_to_tick(sl_price, pair)
+            
+            # ROUND QUANTITY TO STEP SIZE (WITH DECIMAL!)
+            qty_rounded = self._round_quantity(qty, pair)
+            
+            # Place SL order using create_order (correct Binance API method)
+            order = self.client.create_order(
+                symbol=pair,
+                side='SELL',
+                type='STOP_LOSS_LIMIT',
+                timeInForce='GTC',
+                quantity=qty_rounded,
+                stopPrice=sl_price,
+                price=sl_price  # For STOP_LOSS_LIMIT, need price = stopPrice
+            )
+            logger.info(f"🛡️ SL: {pair} x{qty_rounded} @ ${sl_price:.4f} (-{self.STOP_LOSS_PERCENT}%)")
+            
+        except BinanceAPIException as e:
+            logger.error(f"SL Error {pair}: {e}")
+    
+    async def monitor_positions(self):
+        """Monitor open positions for TP/SL"""
+        try:
+            account = self.client.get_account()
+            
+            for pair in list(self.active_trades.keys()):
+                ticker = self.client.get_ticker(symbol=pair)
+                current = float(ticker['lastPrice'])
+                entry = self.active_trades[pair]['entry']
+                
+                gain_percent = ((current - entry) / entry) * 100
+                
+                # Check TP
+                if gain_percent >= self.TAKE_PROFIT_PERCENT:
+                    await self.close_position(pair, 'TP', current)
+                
+                # Check SL (secondary check)
+                elif gain_percent <= -self.STOP_LOSS_PERCENT:
+                    await self.close_position(pair, 'SL', current)
+        
+        except Exception as e:
+            logger.error(f"Monitor Error: {e}")
+    
+    async def close_position(self, pair, reason, current_price):
+        """Close position"""
+        if pair not in self.active_trades:
+            return
+        
+        qty = self.active_trades[pair]['qty']
+        entry = self.active_trades[pair]['entry']
+        pnl = (current_price - entry) * qty
+        
+        logger.info(f"📊 {reason}: {pair} closed @ ${current_price:.2f}, PnL: ${pnl:.2f}")
+        
+        del self.active_trades[pair]
+        self.daily_pnl += pnl
+        
+        if pnl > 0:
+            self.wins_today += 1
+        else:
+            self.losses_today += 1
+        
+        # Check daily loss limit
+        if self.daily_pnl <= self.DAILY_LOSS_LIMIT:
+            logger.warning(f"⚠️ DAILY LOSS LIMIT REACHED: ${self.daily_pnl:.2f}")
+            self.paused = True
+    
+    def get_performance_report(self):
+        """Get current performance metrics"""
+        try:
+            account = self.client.get_account()
+            balance = {}
+            
+            for asset_data in account['balances']:
+                asset = asset_data['asset']
+                free = float(asset_data['free'])
+                locked = float(asset_data['locked'])
+                total = free + locked
+                
+                if total > 0.00001:
+                    balance[asset] = {
+                        'free': free,
+                        'locked': locked,
+                        'total': total
+                    }
+            
+            # Get prices
+            prices = {}
+            for pair in self.PAIRS:
+                try:
+                    ticker = self.client.get_ticker(symbol=pair)
+                    asset = pair.replace('USDT', '')
+                    prices[asset] = float(ticker['lastPrice'])
+                except:
+                    pass
+            prices['USDT'] = 1.0
+            
+            # Calculate portfolio
+            portfolio = 0
+            tracked = ['BTC', 'ETH', 'SOL', 'BNB', 'XRP', 'USDT']
+            for asset in tracked:
+                if asset in balance:
+                    portfolio += balance[asset]['total'] * prices.get(asset, 0)
+            
+            return {
+                'portfolio': round(portfolio, 2),
+                'usdt_free': balance.get('USDT', {}).get('free', 0),
+                'daily_pnl': self.daily_pnl,
+                'trades_today': self.trades_today,
+                'wins': self.wins_today,
+                'losses': self.losses_today,
+                'active_trades': len(self.active_trades),
+                'paused': self.paused
+            }
+        except Exception as e:
+            logger.error(f"Performance Report Error: {e}")
+            return None
+    
+    def swap_coins_to_usdt(self):
+        """
+        AUTO-SWAP: Konvertiere alle freien (unlocked) Coins → USDT
+        Ignoriert locked Coins (von aktiven Trades)
+        Skip-list: LDBTTC (shitcoin), LDDOGE (shitcoin), USDC (dust)
+        """
+        skip_coins = ['USDT', 'LDBTTC', 'LDDOGE', 'USDC']  # Never swap these
+        
+        try:
+            balance = self.client.get_account()
+            
+            swapped_total_usdt = 0
+            swap_log = []
+            
+            for asset in balance['balances']:
+                coin = asset['asset']
+                free_qty = float(asset['free'])
+                
+                # Skip: small amounts, USDT, locked coins, skip-list
+                if free_qty < 0.00001 or coin in skip_coins:
+                    continue
+                
+                try:
+                    symbol = f"{coin}USDT"
+                    
+                    # Get current price to estimate value
+                    ticker = self.client.get_symbol_info(symbol)
+                    if not ticker:
+                        logger.warning(f"No ticker for {symbol}")
+                        continue
+                    
+                    # Round quantity to step size
+                    qty_to_sell = self._round_quantity(free_qty, symbol)
+                    if qty_to_sell < 0.00001:
+                        continue
+                    
+                    # MARKET SELL (immediate)
+                    order = self.client.order_market_sell(symbol=symbol, quantity=qty_to_sell)
+                    
+                    # Calculate USDT received
+                    fills = order.get('fills', [])
+                    usdt_received = sum(float(f['qty']) * float(f['price']) for f in fills)
+                    
+                    swapped_total_usdt += usdt_received
+                    swap_log.append(f"✅ {coin}: {qty_to_sell:.6f} → ${usdt_received:.2f}")
+                    logger.info(f"Sweep: Sold {qty_to_sell} {coin} for ${usdt_received:.2f}")
+                    
+                except BinanceAPIException as e:
+                    logger.warning(f"Sweep {coin}: Binance Error {e.status_code} - {e.message}")
+                    swap_log.append(f"❌ {coin}: {e.message}")
+                except Exception as e:
+                    logger.warning(f"Sweep {coin}: {e}")
+                    swap_log.append(f"❌ {coin}: {str(e)}")
+            
+            # RESULT
+            result = {
+                'success': True,
+                'total_usdt_acquired': swapped_total_usdt,
+                'swaps_attempted': len(swap_log),
+                'log': swap_log
+            }
+            
+            # Send Telegram notification
+            msg = f"""🔄 **COINS TO USDT SWAP COMPLETE**
+
+**Total Converted:** ${swapped_total_usdt:.2f} → USDT
+
+{chr(10).join(swap_log)}
+
+**New USDT Balance:** ${self.get_usdt_balance():.2f}
+"""
+            self._send_telegram(msg)
+            
+            logger.info(f"Swap complete: ${swapped_total_usdt:.2f} converted")
+            return result
+            
+        except Exception as e:
+            logger.error(f"Swap error: {e}")
+            self._send_telegram(f"❌ **SWAP FAILED**: {e}")
+            return {'success': False, 'error': str(e)}
+    
+    def get_usdt_balance(self):
+        """Get current USDT balance"""
+        try:
+            balance = self.client.get_account()
+            for asset in balance['balances']:
+                if asset['asset'] == 'USDT':
+                    return float(asset['free'])
+            return 0.0
+        except:
+            return 0.0
+
+    def send_performance_report(self):
+        """Send 3h performance report via Telegram"""
+        report = self.get_performance_report()
+        if not report:
+            return
+        
+        win_rate = 0
+        if report['trades_today'] > 0:
+            win_rate = (report['wins'] / report['trades_today']) * 100
+        
+        status = "🟢 RUNNING" if not report['paused'] else "⏸️ PAUSED"
+        
+        message = f"""📊 **3H PERFORMANCE REPORT**
+
+**Portfolio Status:**
+• Total: ${report['portfolio']:.2f}
+• USDT Free: ${report['usdt_free']:.2f}
+• Status: {status}
+
+**Today's Trading:**
+• Trades Executed: {report['trades_today']}
+• Wins: {report['wins']} ✅
+• Losses: {report['losses']} ❌
+• Win Rate: {win_rate:.1f}%
+
+**P&L:**
+• Daily P&L: ${report['daily_pnl']:.2f}
+• Open Positions: {report['active_trades']}
+
+**Risk Status:**
+• Daily Loss Limit: -5%
+• Current Daily Loss: ${report['daily_pnl']:.2f}
+• Pause Active: {'Yes ⏸️' if report['paused'] else 'No ✅'}
+
+---
+Time: {datetime.now().strftime('%Y-%m-%d %H:%M UTC')}
+Bot: V0.2 Adaptive"""
+        
+        self._send_telegram(message)
+        logger.info("📱 Performance report sent to Telegram")
+    
+    async def run_cycle(self):
+        """Main trading cycle"""
+        last_report_hour = None
+        
+        while True:
+            try:
+                # Check if it's time for 3h report
+                current_hour = datetime.now().hour
+                if current_hour % 3 == 0 and last_report_hour != current_hour:
+                    self.send_performance_report()
+                    last_report_hour = current_hour
+                
+                # Check daily loss limit pause
+                if self.paused:
+                    logger.info("⏸️ Bot PAUSED (daily loss limit reached)")
+                    await asyncio.sleep(60)
+                    continue
+                
+                # Signal generation
+                for pair in self.PAIRS:
+                    if pair not in self.active_trades and await self.signal_buy(pair):
+                        await self.place_buy_order(pair)
+                
+                # Monitor positions
+                await self.monitor_positions()
+                
+                await asyncio.sleep(5)
+                
+            except Exception as e:
+                logger.error(f"Cycle Error: {e}")
+                await asyncio.sleep(5)
+
+async def main():
+    bot = TradingBot()
+    await bot.run_cycle()
+
+if __name__ == '__main__':
+    asyncio.run(main())
+
+
+    def get_signal_confidence(self):
+        """Calculate confidence level for current signal (0-100%)"""
+        # This can be enhanced with actual ML model
+        # For now: random 30-95%
+        import random
+        return random.uniform(30, 95)
+    
+    def get_investment_percent(self, confidence):
+        """Select investment % based on confidence"""
+        return self.INVESTMENT_PERCENT_HIGH if confidence > self.CONFIDENCE_THRESHOLD else self.INVESTMENT_PERCENT
+    
+    def check_consecutive_loss_cooldown(self):
+        """Check if bot is in cooldown after 3 consecutive losses"""
+        if self.consecutive_losses >= self.MAX_CONSECUTIVE_LOSSES:
+            if self.last_loss_time is None:
+                return False  # First loss, no cooldown
+            
+            time_elapsed = time.time() - self.last_loss_time
+            if time_elapsed < self.CONSECUTIVE_LOSS_COOLDOWN:
+                logger.warning(f"🚫 Cooldown active: {int(self.CONSECUTIVE_LOSS_COOLDOWN - time_elapsed)}s remaining")
+                return False
+            else:
+                # Cooldown expired, reset counter
+                self.consecutive_losses = 0
+                logger.info("✅ Cooldown expired, consecutive loss counter reset")
+                return True
+        return True
+    
+    def check_volatility(self, pair):
+        """Check market volatility (simplified)"""
+        try:
+            ticker = self.client.get_symbol_ticker(symbol=pair)
+            current_price = float(ticker['price'])
+            
+            # Get 1h candle for volatility estimate
+            candles = self.client.get_klines(symbol=pair, interval='1h', limit=5)
+            
+            high_prices = [float(c[2]) for c in candles]
+            low_prices = [float(c[3]) for c in candles]
+            
+            volatility = (max(high_prices) - min(low_prices)) / min(low_prices) * 100
+            
+            # Flag as extreme if > 5% 1h volatility
+            if volatility > 5:
+                logger.warning(f"⚠️ High volatility {pair}: {volatility:.2f}% (skipping trade)")
+                return False
+            return True
+        except:
+            return True  # If check fails, allow trade
+    
+    def check_daily_trade_limit(self):
+        """Check if daily trade limit reached"""
+        import datetime
+        
+        now = datetime.datetime.now()
+        today_start = now.replace(hour=0, minute=0, second=0, microsecond=0)
+        
+        if self.last_trade_reset is None or self.last_trade_reset < today_start:
+            self.trades_today = 0
+            self.last_trade_reset = now
+        
+        if self.trades_today >= self.MAX_TRADES_PER_DAY:
+            logger.warning(f"⚠️ Daily limit reached: {self.trades_today}/{self.MAX_TRADES_PER_DAY} trades")
+            return False
+        
+        return True
+    
+    def update_trailing_stop(self, pair, current_price, entry_price):
+        """Update trailing stop for an open position"""
+        if pair not in self.active_trades:
+            return False
+        
+        trade_data = self.active_trades[pair]
+        profit_pct = ((current_price - entry_price) / entry_price) * 100
+        
+        # Activate trailing stop when profit >= 1.5%
+        if profit_pct >= self.TRAILING_STOP_ENTRY:
+            trailing_stop_price = current_price * (1 - self.TRAILING_STOP_DISTANCE / 100)
+            trade_data['trailing_stop'] = trailing_stop_price
+            
+            # If price falls below trailing stop, close position
+            if current_price < trailing_stop_price:
+                logger.info(f"🛑 Trailing stop triggered {pair}: Sell @ ${current_price:.2f}")
+                return True
+        
+        return False
+
+
+    def record_entry(self, pair, price, quantity):
+        """Record entry price for profit calculation"""
+        self.entry_price_history[pair] = {
+            'price': price,
+            'qty': quantity,
+            'value': price * quantity,
+            'timestamp': time.time()
+        }
+    
+    def calculate_unrealized_pnl(self):
+        """Calculate unrealized P&L for open positions"""
+        try:
+            prices = get_live_prices()
+            total_unrealized = 0
+            
+            for pair, entry_data in self.entry_price_history.items():
+                asset = pair.replace('USDT', '')
+                current_price = prices.get(asset, 0)
+                if current_price > 0:
+                    current_value = entry_data['qty'] * current_price
+                    unrealized = current_value - entry_data['value']
+                    total_unrealized += unrealized
+            
+            return total_unrealized
+        except:
+            return 0
+    
+    def calculate_realized_pnl(self):
+        """Sum all closed trades realized P&L"""
+        return sum(t.get('profit_usdt', 0) for t in self.closed_trades)
+    
+    def get_total_pnl(self):
+        """Total P&L = realized + unrealized"""
+        return self.calculate_realized_pnl() + self.calculate_unrealized_pnl()
+