XAU-60

MT5 Trading Bot Pro v2.0

A professional-grade, modular trading bot for MetaTrader 5 with a modern Streamlit web interface. Features multi-account management, advanced risk controls, and production-ready trading strategies.

What’s New in v2.0

• Multi-Account Management - Securely manage multiple MT5 accounts with encrypted credential storage
• Professional Trading Dashboard - Real-time candlestick charts, live positions, and manual trading panel
• Strategy Builder - Visual strategy creation, deployment, and monitoring
• Advanced Trade Executor - Trailing stops, break-even, partial closes, and order retry logic
• Enhanced Risk Management - Circuit breaker, correlation exposure limits, and real-time risk monitoring
• Signal Quality Scoring - Each strategy rates signals (A+, A, B, C, D) for trade confidence
• Improved Backtesting - Strategy comparison, equity curves, and CSV export

Features

Core Features

• Modular Strategy System - Add new strategies by creating a Python file + YAML config
• Multi-Symbol Support - Trade XAUUSD, EURUSD, GBPUSD, and more simultaneously
• Smart Money Concepts - Built-in CHoCH, FVG, Order Block detection
• Backtesting Engine - Test strategies on historical data with detailed metrics
• Real-time Alerts - Telegram and Discord notifications
• Web UI - Modern Streamlit dashboard for monitoring and configuration

Advanced Features (v2.0)

• Encrypted Account Storage - Fernet encryption for MT5 credentials
• Auto-Reconnect - Health monitoring with automatic reconnection
• Circuit Breaker - Pauses trading after consecutive losses
• Trailing Stops - Automatic trailing stop management
• Break-Even - Move stop loss to entry when in profit
• Partial Close - Close portions of positions at targets
• Correlation Risk - Limits exposure to correlated pairs

Project Structure

├── main.py                     # Entry point
├── requirements.txt            # Python dependencies
├── .env.example               # Environment variables template
├── config/
│   ├── settings.yaml          # Global settings
│   └── strategies/            # Strategy configurations
├── core/
│   ├── strategy_base.py       # Abstract Strategy class
│   ├── mt5_connector.py       # MT5 API wrapper with multi-account
│   ├── account_manager.py     # Encrypted account management
│   ├── trade_executor.py      # Advanced order execution
│   ├── risk_manager.py        # Comprehensive risk controls
│   ├── strategy_loader.py     # Dynamic strategy discovery
│   └── backtest_engine.py     # Backtesting
├── strategies/
│   ├── __init__.py            # Strategy registry
│   ├── smc_scalper.py         # SMC Scalper strategy
│   ├── trend_break_trauma.py  # Trend Break + RSI strategy
│   └── crt_tbs.py             # CRT + TBS strategy
├── indicators/
│   ├── common.py              # RSI, EMA, ATR, MACD, etc.
│   ├── smc_utils.py           # CHoCH, FVG, Order Blocks
│   └── trend_utils.py         # Trend line detection
├── alerts/
│   ├── telegram_bot.py        # Telegram notifications
│   └── discord_bot.py         # Discord webhooks
├── ui/
│   ├── app.py                 # Streamlit main app
│   └── pages/
│       ├── dashboard.py       # Live trading dashboard
│       ├── strategies.py      # Strategy management
│       ├── strategy_builder.py # Visual strategy builder
│       ├── backtest.py        # Backtesting interface
│       ├── accounts.py        # Multi-account management
│       └── settings.py        # Configuration
└── utils/
    ├── config.py              # Environment config loader
    ├── logger.py              # Logging setup
    └── helpers.py             # Utility functions

Quick Start

1. Install Dependencies

pip install -r requirements.txt

Note: MetaTrader5 package only works on Windows. For macOS/Linux, use the mock MT5 module for development and backtesting.

2. Configure Environment Variables

Copy .env.example to .env and fill in your credentials:

cp .env.example .env

Edit .env with your settings:

# MetaTrader 5 (Primary Account)
MT5_LOGIN=your_account_number
MT5_PASSWORD=your_password
MT5_SERVER=YourBroker-Demo

# Optional: Encryption key for account storage
# Generate: python -c "from cryptography.fernet import Fernet; print(Fernet.generate_key().decode())"
ENCRYPTION_KEY=

# Risk Management
MAX_RISK_PER_TRADE=2.0
MAX_DAILY_LOSS=5.0
MAX_DRAWDOWN=20.0
CIRCUIT_BREAKER_CONSECUTIVE_LOSSES=3

# Alerts (optional)
TELEGRAM_ENABLED=false
TELEGRAM_BOT_TOKEN=your_bot_token
TELEGRAM_CHAT_ID=your_chat_id

Important: Never commit .env to version control!

3. Run the Bot

Web UI Mode (Recommended):

streamlit run ui/app.py

CLI Mode (Live Trading):

python main.py

Dry Run (Test Configuration):

python main.py --dry-run

Included Strategies

All strategies include signal quality scoring (A+, A, B, C, D) based on multiple confirmation factors.

1. SMC Scalper v2.1

Smart Money Concepts based scalping strategy with confidence scoring.

Feature	Details
Entry	CHoCH + FVG confluence + Order Block target
Confirmations	MTF trend, ADX strength, RSI momentum, session timing
Exit	Order Block target, opposing CHoCH, or R:R ratio
Timeframe	M15
Best for	XAUUSD during London/NY session

Quality Scoring Factors:

• CHoCH detected (2 pts)
• FVG detected (2 pts)
• Order Block valid (1 pt)
• Trend aligned (2 pts)
• Price in FVG zone (1 pt)
• Session optimal (1 pt)
• ADX filter passed (1 pt)
• RSI filter passed (1 pt)
• Spread acceptable (1 pt)

2. Trend Break + Trauma + RSI v2.1

Trend line breakout strategy with EMA filter and momentum confirmation.

Feature	Details
Entry	Price above/below Trauma (EMA21) + Trend break + Displacement
Confirmations	EMA stack (8/21/50), MACD alignment, ADX strength, volume spike
Exit	RSI overbought/oversold or divergence detection
Timeframe	H1
Best for	Trending markets

Quality Scoring Factors:

• Trendline break (2 pts)
• Price above Trauma (2 pts)
• Breakout displacement (2 pts)
• EMA stack aligned (1 pt)
• MACD aligned (1 pt)
• ADX strong trend (1 pt)
• RSI momentum aligned (1 pt)
• Session optimal (1 pt)

3. CRT + TBS v2.1 (Candle Range Theory + Time-Based Strategy)

Asian session range + killzone liquidity sweep strategy with manipulation quality scoring.

Feature	Details
Range	Asian Session (00:00-06:00 UTC) defines High/Low
Killzones	London (07:00-09:00), NY (13:00-15:00), London Close (optional)
Entry	Price sweeps beyond range, closes back inside with confirmation
Exit	Opposite end of Asian range or time-based exit
Timeframe	M5 entry, H1 range
Best for	XAUUSD during high-volatility sessions

Sweep Quality Levels:

• Perfect - Textbook manipulation with strong rejection
• Strong - Clear sweep with displacement
• Moderate - Decent sweep with momentum
• Weak - Small sweep, quick return

UI Pages

Dashboard

• Real-time account metrics (balance, equity, profit)
• Interactive candlestick chart with EMA overlays
• Live positions table with close buttons
• Manual trading panel (Buy/Sell with SL/TP)

Strategy Builder

• Visual strategy list with enable/disable toggles
• Live parameter editing
• Deploy/undeploy strategies
• Strategy performance monitoring

Backtest

• Single strategy backtesting
• Strategy comparison mode
• Equity curve visualization
• Drawdown analysis
• Trade distribution charts
• CSV export

Accounts

• Add/remove MT5 accounts
• Encrypted credential storage
• Quick account switching
• Connection health monitoring

Settings

• Risk parameters configuration
• Alert settings
• UI preferences

Multi-Account Management

Add multiple MT5 accounts with encrypted storage:

from core.account_manager import get_account_manager

manager = get_account_manager()

# Add account (credentials are encrypted)
manager.add_account(
    name="My Demo Account",
    login=12345678,
    password="secure_password",
    server="Broker-Demo"
)

# Switch between accounts
accounts = manager.list_accounts()
manager.switch_account(accounts[0].id)

# Connect to active account
manager.connect()

Or use the Accounts page in the UI for a visual interface.

Advanced Risk Management

Position Sizing

# Formula: lot = (balance * risk%) / (sl_pips * pip_value)
lot_size = risk_manager.calculate_lot_size(
    symbol="XAUUSD",
    stop_loss_pips=50,
    risk_percent=2.0
)

Circuit Breaker

Automatically pauses trading after consecutive losses:

CIRCUIT_BREAKER_ENABLED=true
CIRCUIT_BREAKER_CONSECUTIVE_LOSSES=3
CIRCUIT_BREAKER_COOLDOWN_MINUTES=60

Risk Limits

from core.risk_manager import RiskLimits

limits = RiskLimits(
    max_risk_per_trade=2.0,
    max_daily_loss=5.0,
    max_drawdown=20.0,
    max_positions=5,
    max_lot_size=1.0,
    max_correlated_exposure=3.0,
    circuit_breaker_losses=3
)

Trade Execution Features

Trailing Stop

from core.trade_executor import get_trade_executor, TrailingStopConfig

executor = get_trade_executor()
executor.enable_trailing_stop(
    ticket=12345,
    config=TrailingStopConfig(
        activation_pips=30,
        trailing_distance_pips=20,
        step_pips=5
    )
)

Break-Even

from core.trade_executor import BreakEvenConfig

executor.set_break_even(
    ticket=12345,
    config=BreakEvenConfig(
        trigger_pips=20,
        offset_pips=2
    )
)

Partial Close

executor.partial_close(ticket=12345, percent=50)

Adding New Strategies

Step 1: Create Strategy File

Create strategies/my_strategy.py:

from core.strategy_base import StrategyBase, Signal, TradeSignal, Position
import pandas as pd
from typing import Optional, Dict, Any
from dataclasses import dataclass

@dataclass
class MyConfirmation:
    """Track confirmations for signal quality."""
    condition_1: bool = False
    condition_2: bool = False

    @property
    def score(self) -> int:
        return sum([self.condition_1 * 2, self.condition_2 * 1])

    @property
    def quality(self) -> str:
        if self.score >= 3: return "A"
        elif self.score >= 2: return "B"
        else: return "C"

class MyStrategy(StrategyBase):
    name = "My Strategy"
    version = "1.0.0"
    description = "My custom trading strategy"

    def initialize(self, config: Dict[str, Any]) -> None:
        self.config = config
        self.symbols = config.get("symbols", ["XAUUSD"])
        self.timeframe = config.get("timeframe", "M15")
        self.enabled = config.get("enabled", True)
        self.min_quality = config.get("filters", {}).get("min_quality", "B")

    def analyze(self, symbol: str, data: pd.DataFrame) -> Optional[TradeSignal]:
        confirmation = MyConfirmation()

        # Your entry logic
        confirmation.condition_1 = your_check_1(data)
        confirmation.condition_2 = your_check_2(data)

        # Check minimum quality
        quality_order = {"A": 3, "B": 2, "C": 1}
        if quality_order.get(confirmation.quality, 0) < quality_order.get(self.min_quality, 2):
            return None

        if confirmation.condition_1:
            return TradeSignal(
                signal=Signal.BUY,
                symbol=symbol,
                entry_price=data.iloc[-1]["close"],
                stop_loss=stop_loss_price,
                take_profit=take_profit_price,
                comment=f"MyStrategy_BUY_{confirmation.quality}"
            )
        return None

    def should_close(self, position: Position, data: pd.DataFrame) -> bool:
        return False

Step 2: Create Config File

Create config/strategies/my_strategy.yaml:

name: "My Strategy"
enabled: true
description: "My custom trading strategy"

symbols:
  - XAUUSD

timeframe: M15
magic_number: 123456

parameters:
  my_param: 10
  another_param: 2.5

filters:
  min_quality: "B"
  use_adx: true
  adx_threshold: 20

risk:
  max_risk_percent: 2.0
  lot_size: 0.01

session:
  start_hour: 8
  end_hour: 18
  trade_friday: false

Step 3: Register Strategy

Add to strategies/__init__.py:

from .my_strategy import MyStrategy

STRATEGY_REGISTRY = {
    # ... existing strategies
    "My Strategy": MyStrategy,
}

Environment Variables Reference

Variable	Description	Default
MT5_LOGIN	MT5 account number	-
MT5_PASSWORD	MT5 password	-
MT5_SERVER	MT5 broker server	-
ENCRYPTION_KEY	Fernet key for credential encryption	Auto-generated
MAX_RISK_PER_TRADE	Max risk per trade (%)	2.0
MAX_DAILY_LOSS	Max daily loss (%)	5.0
MAX_DRAWDOWN	Max drawdown (%)	20.0
CIRCUIT_BREAKER_CONSECUTIVE_LOSSES	Losses before pause	3
CIRCUIT_BREAKER_COOLDOWN_MINUTES	Cooldown duration	60
TRAILING_STOP_ENABLED	Enable trailing stops	true
BREAKEVEN_ENABLED	Enable break-even	true
TELEGRAM_ENABLED	Enable Telegram alerts	false
DISCORD_ENABLED	Enable Discord alerts	false

Requirements

• Python 3.9+
• MetaTrader 5 terminal (Windows only for live trading)
• MT5 account with broker

Dependencies

• MetaTrader5 (Windows)
• pandas, numpy
• streamlit, plotly
• cryptography (Fernet encryption)
• pyyaml, python-dotenv
• python-telegram-bot
• requests
• ta (technical analysis)
• loguru
• pytz

Risk Warning

Trading involves significant risk of loss. This software is for educational purposes. Always:

• Test on demo accounts first
• Use conservative risk settings (1-2% per trade)
• Never risk more than you can afford to lose
• Past performance doesn’t guarantee future results

License

This project is licensed under the MIT License - see the LICENSE file for details.

Disclaimer: Trading involves significant risk. Use at your own risk.

Support

For issues and feature requests, create an issue on GitHub.

Changelog

v2.0.0

• Added multi-account management with encrypted storage
• New professional trading dashboard with live charts
• Strategy builder page for visual strategy creation
• Advanced trade executor (trailing stops, break-even, partial close)
• Enhanced risk manager (circuit breaker, correlation limits)
• Signal quality scoring for all strategies
• Strategy comparison in backtesting
• Cross-platform support (mock MT5 for macOS/Linux development)