diff --git a/src/main_ml.py b/src/main_ml.py index 4370cb3..e5c9013 100644 --- a/src/main_ml.py +++ b/src/main_ml.py @@ -30,12 +30,31 @@ class TradingBot: 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 = 5 # 5% random signal - self.INVESTMENT_PERCENT = 35 # 35% per trade (5 parallel = 90% max, 10% buffer) + self.SIGNAL_THRESHOLD = 7.5 # 7-8% range (midpoint 7.5%) # 5% random signal + self.INVESTMENT_PERCENT = 25 # 25% standard + self.INVESTMENT_PERCENT_HIGH = 35 # 35% when confidence > 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 = 2.5 # -2.5% - self.TAKE_PROFIT_PERCENT = 3.0 # +3% - self.DAILY_LOSS_LIMIT = -5 # -5% max + 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 = 3 # 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 self.active_trades = {} self.daily_pnl = 0 @@ -53,7 +72,7 @@ class TradingBot: self.telegram_token = env.get('TELEGRAM_BOT_TOKEN') self.telegram_chat_id = env.get('TELEGRAM_CHAT_ID') - logger.info("βœ… Bot initialized with Risk Management (SL 2.5%, TP 3%, Daily Limit 5%)") + logger.info(f"βœ… 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() @@ -231,7 +250,7 @@ Reports: Alle 3h via Telegram πŸ“Š""" async def place_stop_loss(self, pair, entry_price, qty): """Place stop loss order with correct precision & API method""" try: - # Calculate SL price with 2.5% loss + # 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!) @@ -432,3 +451,91 @@ async def main(): 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("βœ… 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"πŸ›‘ Trailing stop triggered {pair}: Sell @ ${current_price:.2f}") + return True + + return False diff --git a/src/main_ml.py.backup.35pct.20240706 b/src/main_ml.py.backup.35pct.20240706 new file mode 100644 index 0000000..4370cb3 --- /dev/null +++ b/src/main_ml.py.backup.35pct.20240706 @@ -0,0 +1,434 @@ +#!/usr/bin/env python3 +""" +Trading Bot V5 ENHANCED - FULLY FIXED VERSION +Implementiert: SL, TP, Daily Limit, R:R Ratio +FIXED: Binance API method (order_take_profit β†’ create_order) +FIXED: PRICE_FILTER fΓΌr SL Orders durch Tick-Rounding +FIXED: Quantity rounding mit Decimal (no floating point errors) +FIXED: Quantity string formatting fΓΌr 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 = 5 # 5% random signal + self.INVESTMENT_PERCENT = 35 # 35% per trade (5 parallel = 90% max, 10% buffer) + self.NOTIONAL_MIN = 5.0 # Override Binance minimum to $3 + self.STOP_LOSS_PERCENT = 2.5 # -2.5% + self.TAKE_PROFIT_PERCENT = 3.0 # +3% + self.DAILY_LOSS_LIMIT = -5 # -5% max + + self.active_trades = {} + self.daily_pnl = 0 + self.paused = False + 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("βœ… Bot initialized with Risk Management (SL 2.5%, TP 3%, Daily Limit 5%)") + + # 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 = """πŸ€– **TRADING BOT V5 β€” STARTED!** + +βš™οΈ **AKTUELLE STRATEGIE:** + +**Entry:** +β€’ Signal: 5% Random (5 sec cycle) +β€’ Investment: 18% USDT per trade ← FIXED! +β€’ Pairs: BTC, ETH, SOL, BNB, XRP +β€’ Max Parallel: 5 trades (5Γ—18% = 90% max) + +**Exit:** +β€’ Take Profit: +3.0% βœ… +β€’ Stop Loss: -2.5% βœ… +β€’ Risk/Reward: 1:1.2 + +**Risk Management:** +β€’ Daily Loss Limit: -5% +β€’ Position Size Cap: 18% +β€’ Buffer Reserve: 10% USDT +β€’ SL Auto-Place: Ja (korrekt gerundet) + +**Status:** 🟒 LIVE +β€’ Time: """ + datetime.now().strftime('%Y-%m-%d %H:%M UTC') + """ +β€’ Capital Ready: 100% USDT + +--- +Reports: Alle 3h via Telegram πŸ“Š""" + + self._send_telegram(message) + logger.info("πŸ“± 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"βœ… 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 2.5% 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"πŸ›‘οΈ 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"πŸ“Š {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 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"""πŸ“Š **3H PERFORMANCE REPORT** + +**Portfolio Status:** +β€’ Total: ${report['portfolio']:.2f} +β€’ USDT Free: ${report['usdt_free']:.2f} +β€’ Status: {status} + +**Today's Trading:** +β€’ Trades Executed: {report['trades_today']} +β€’ Wins: {report['wins']} βœ… +β€’ Losses: {report['losses']} ❌ +β€’ Win Rate: {win_rate:.1f}% + +**P&L:** +β€’ Daily P&L: ${report['daily_pnl']:.2f} +β€’ Open Positions: {report['active_trades']} + +**Risk Status:** +β€’ Daily Loss Limit: -5% +β€’ Current Daily Loss: ${report['daily_pnl']:.2f} +β€’ Pause Active: {'Yes ⏸️' if report['paused'] else 'No βœ…'} + +--- +Time: {datetime.now().strftime('%Y-%m-%d %H:%M UTC')} +Bot: V5 ENHANCED (FULLY FIXED)""" + + self._send_telegram(message) + logger.info("πŸ“± 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())