GitHub - yeahrb/CEX-Option-Futures-Crypto-Quant-Algorithm-Trading-Bot: https://t.me/yeahrbb Automated cex option futures spot algorithm crypto quant binance bitget bybit kucoin trading bot binance trading bot binance trading bot binance trading bot binance trading bot binance trading bot binance trading bot binance trading bot binance trading bot binance trading bot binance trading bot binance trading bot binance bot

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🚀 CEX Option Futures Stock Quant Algorithm Trading Bot

📋 Table of Contents

🌟 Features

🎯 Core Trading Capabilities

  • Multi-Exchange Support: Trade on Binance, Bitget, Bybit, and more
  • Advanced Order Management: Limit orders, market orders, stop-loss, take-profit
  • Real-time Market Data: Live price feeds, order book analysis, volume tracking
  • Risk Management: Built-in stop-loss, position sizing, portfolio protection
  • Backtesting Engine: Test strategies with historical data before live trading

🧠 Trading Algorithms

  • Profit Hunter Mode: Automated profit-taking based on predefined percentages
  • Range Trading: Buy low, sell high within specified price ranges
  • Arbitrage Detection: Cross-exchange price difference exploitation
  • Grid Trading: Systematic buy/sell orders at predetermined intervals
  • DCA (Dollar Cost Averaging): Automated periodic investments
  • Momentum Trading: Trend-following strategies with technical indicators

🔧 Technical Features

  • Multi-threading: Concurrent order processing and market analysis
  • Database Integration: SQLite for trade history and performance tracking
  • Logging System: Comprehensive logging for debugging and analysis
  • API Rate Limiting: Intelligent request throttling to prevent bans
  • Error Handling: Robust error recovery and fail-safe mechanisms
  • Configuration Management: Flexible parameter adjustment without code changes

📊 Analytics & Monitoring

  • Real-time P&L Tracking: Live profit/loss monitoring
  • Performance Metrics: Win rate, Sharpe ratio, maximum drawdown
  • Trade History: Complete transaction logging and analysis
  • Balance Monitoring: Multi-asset portfolio tracking
  • Market Scanner: Automated opportunity detection across pairs

🏢 Supported Exchanges

Exchange Status Features
Binance ✅ Fully Supported Spot, Futures, Options
Bitget ✅ Fully Supported Spot, Futures, Copy Trading
Bybit ✅ Fully Supported Spot, Derivatives, Options
OKX 🔄 In Development Spot, Futures, Options
KuCoin 🔄 In Development Spot, Futures
Gate.io 📋 Planned Spot, Futures

📈 Supported Trading Pairs

  • Cryptocurrency: BTC, ETH, BNB, ADA, SOL, MATIC, and 1000+ altcoins
  • Fiat Pairs: USDT, USDC, BUSD, EUR, GBP, JPY
  • Cross Pairs: BTC/ETH, ETH/BNB, and custom combinations
  • Futures: Perpetual contracts with leverage up to 125x
  • Options: Call/Put options with various strike prices

⚡ Trading Algorithms

🎯 1. Profit Hunter Algorithm

# Automated profit-taking strategy
python trader.py --symbol BTCUSDT --profit 2.5 --quantity 0.01
  • Description: Monitors market spreads and executes trades when profit targets are met
  • Best For: High-frequency trading, scalping strategies
  • Risk Level: Medium
  • Expected Returns: 1-5% per trade

📊 2. Range Trading Algorithm

# Buy low, sell high within ranges
python trader.py --symbol ETHUSDT --mode range --buyprice 1800 --sellprice 1850
  • Description: Identifies support/resistance levels and trades within ranges
  • Best For: Sideways markets, consolidation periods
  • Risk Level: Low-Medium
  • Expected Returns: 0.5-3% per cycle

🔄 3. Grid Trading Algorithm

# Systematic grid orders
python trader.py --symbol ADAUSDT --mode grid --grid_size 0.01 --levels 10
  • Description: Places buy/sell orders at predetermined price intervals
  • Best For: Volatile markets with clear ranges
  • Risk Level: Medium
  • Expected Returns: 2-8% per grid cycle

📈 4. Momentum Trading Algorithm

# Trend-following with technical indicators
python trader.py --symbol SOLUSDT --mode momentum --indicator RSI --threshold 70
  • Description: Uses technical indicators to identify trend continuations
  • Best For: Trending markets, breakout strategies
  • Risk Level: High
  • Expected Returns: 5-15% per trend

💰 5. DCA (Dollar Cost Averaging)

# Automated periodic investments
python trader.py --symbol BTCUSDT --mode dca --amount 100 --interval daily
  • Description: Regular investments regardless of market conditions
  • Best For: Long-term investors, reducing volatility impact
  • Risk Level: Low
  • Expected Returns: Market average over time

🚀 Quick Start

Prerequisites

  • Python 3.7 or higher
  • API keys from supported exchanges
  • Minimum 0.001 BTC or equivalent for testing

1. Clone the Repository

git clone https://github.com/yeahrb/CEX-Option-Futures-Stock-Quant-Algorithm-Trading-Bot.git
cd CEX-Option-Futures-Stock-Quant-Algorithm-Trading-Bot

2. Install Dependencies

pip install -r requirements.txt

3. Configure API Keys

cp app/config.sample.py app/config.py
# Edit config.py with your API credentials

4. Run Your First Trade

python trader.py --symbol BTCUSDT --profit 1.5 --quantity 0.001

📖 Installation

Method 1: Direct Installation

# Clone repository
git clone https://github.com/yeahrb/CEX-Option-Futures-Stock-Quant-Algorithm-Trading-Bot.git
cd CEX-Option-Futures-Stock-Quant-Algorithm-Trading-Bot

# Install Python dependencies
pip install requests sqlite3 threading argparse logging

# Set up configuration
cp app/config.sample.py app/config.py
cp db/orders.sample.db db/orders.db

# Edit configuration file
nano app/config.py

Method 2: Docker Installation

# Build Docker image
docker build -t cex-trading-bot .

# Run container
docker run -d --name trading-bot cex-trading-bot

# View logs
docker logs -f trading-bot

Method 3: Virtual Environment (Recommended)

# Create virtual environment
python -m venv trading_env
source trading_env/bin/activate  # On Windows: trading_env\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Run the bot
python trader.py --symbol BTCUSDT --profit 2.0

⚙️ Configuration

API Configuration (app/config.py)

# Exchange API Credentials
api_key = 'your_api_key_here'
api_secret = 'your_secret_key_here'

# Optional: Advanced Settings
recv_window = 5000  # Request timeout window
test_mode = False   # Enable test mode (paper trading)
debug_mode = True   # Enable debug logging

Trading Parameters

# Default trading settings
DEFAULT_PROFIT = 1.3          # Default profit percentage
DEFAULT_QUANTITY = 0          # Auto-calculate if 0
DEFAULT_WAIT_TIME = 0.7       # Seconds between checks
DEFAULT_STOP_LOSS = 0         # Stop-loss percentage (0 = disabled)
MAX_TRADE_SIZE = 7           # Maximum concurrent trades

💡 Usage Examples

Basic Trading Examples

1. Simple Profit Taking

# Trade BTC with 2% profit target
python trader.py --symbol BTCUSDT --profit 2.0 --quantity 0.01

2. Range Trading

# Buy at $1800, sell at $1850
python trader.py --symbol ETHUSDT --mode range --buyprice 1800 --sellprice 1850 --quantity 0.1

3. Stop-Loss Protection

# Trade with 5% stop-loss
python trader.py --symbol ADAUSDT --profit 3.0 --stop_loss 5.0 --quantity 100

4. Amount-Based Trading

# Trade with $100 worth of BTC
python trader.py --symbol BTCUSDT --amount 100 --profit 1.5

Advanced Examples

5. Multi-Symbol Trading

# Run multiple bots simultaneously
python trader.py --symbol BTCUSDT --profit 1.5 --quantity 0.01 &
python trader.py --symbol ETHUSDT --profit 2.0 --quantity 0.1 &
python trader.py --symbol ADAUSDT --profit 3.0 --quantity 100 &

6. Debug Mode

# Enable detailed logging
python trader.py --symbol BTCUSDT --profit 2.0 --debug --prints True

7. Limited Loop Trading

# Run for 100 cycles only
python trader.py --symbol BTCUSDT --profit 1.5 --loop 100

Balance Management

# Check account balances
python balance.py

# View specific balance
python balance.py --asset BTC

# Monitor open orders
python balance.py --orders BTCUSDT

📊 Advanced Features

🔍 Market Analysis Tools

  • Order Book Analysis: Real-time bid/ask spread monitoring
  • Volume Analysis: Trading volume pattern recognition
  • Price Action: Support/resistance level detection
  • Technical Indicators: RSI, MACD, Moving Averages integration

📈 Performance Tracking

  • P&L Dashboard: Real-time profit/loss monitoring
  • Trade Statistics: Win rate, average profit, drawdown analysis
  • Risk Metrics: Sharpe ratio, maximum drawdown, volatility
  • Portfolio Analytics: Asset allocation, correlation analysis

🛡️ Risk Management

  • Position Sizing: Automatic position size calculation
  • Stop-Loss Orders: Dynamic stop-loss adjustment
  • Portfolio Limits: Maximum exposure per asset/strategy
  • Emergency Stop: Manual/automatic trading halt

🔧 Customization Options

  • Strategy Parameters: Adjustable profit targets, stop-losses
  • Time Frames: Configurable trading intervals
  • Asset Selection: Custom trading pair selection
  • Notification System: Email/SMS alerts for important events

🐳 Docker Support

Docker Compose Setup

version: '3.8'
services:
  trading-bot:
    build: .
    container_name: cex-trading-bot
    environment:
      - API_KEY=${API_KEY}
      - API_SECRET=${API_SECRET}
    volumes:
      - ./logs:/app/logs
      - ./db:/app/db
    restart: unless-stopped

Docker Commands

# Build and run
docker-compose up -d

# View logs
docker-compose logs -f

# Stop bot
docker-compose down

# Update bot
docker-compose pull && docker-compose up -d

📈 Performance Monitoring

Real-time Monitoring

# Monitor active trades
python monitor.py --live

# View performance metrics
python analytics.py --period 30d

# Generate reports
python report.py --format pdf --period 7d

Key Metrics Tracked

  • Win Rate: Percentage of profitable trades
  • Average Profit: Mean profit per successful trade
  • Maximum Drawdown: Largest peak-to-trough decline
  • Sharpe Ratio: Risk-adjusted return measure
  • Total Return: Overall portfolio performance

🔧 API Documentation

Core Classes

Trading Class

class Trading:
    def __init__(self, options):
        # Initialize trading parameters
        
    def buy(self, symbol, quantity, price):
        # Execute buy order
        
    def sell(self, symbol, quantity, price):
        # Execute sell order
        
    def run(self):
        # Main trading loop

BinanceAPI Class

class BinanceAPI:
    def get_ticker(self, symbol):
        # Get current price
        
    def get_order_book(self, symbol):
        # Get order book data
        
    def place_order(self, symbol, side, quantity, price):
        # Place trading order

Available Methods

  • get_account(): Retrieve account information
  • get_balances(): Get asset balances
  • get_open_orders(): List active orders
  • get_trade_history(): Retrieve trade history
  • cancel_order(): Cancel specific order

🤝 Contributing

We welcome contributions from the community! Here's how you can help:

How to Contribute

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

Contribution Guidelines

  • Follow PEP 8 Python style guidelines
  • Add tests for new features
  • Update documentation for API changes
  • Ensure backward compatibility
  • Include clear commit messages

Areas for Contribution

  • New Exchange Integrations: Add support for additional exchanges
  • Trading Algorithms: Implement new trading strategies
  • UI/UX Improvements: Enhance user interface
  • Documentation: Improve guides and examples
  • Bug Fixes: Report and fix issues
  • Performance Optimization: Improve bot efficiency

📞 Support & Contact

🆘 Getting Help

Discord Community

  • Server: Join our Discord
  • Channels:
    • #general - General discussions
    • #trading-strategies - Strategy sharing
    • #technical-support - Bug reports and help
    • #announcements - Bot updates and news

Telegram Channel

  • Channel: @yeahrbb
  • Group: @yeahrbb
  • Updates: Real-time notifications and market insights

Email Support

📋 Support Response Times

  • Critical Issues: Within 2 hours
  • General Support: Within 24 hours
  • Feature Requests: Within 1 week
  • Bug Reports: Within 48 hours

🔧 Troubleshooting

Common Issues

  1. API Connection Errors

    # Check API credentials
python test_connection.py

  2. Order Execution Failures

    # Enable debug mode
python trader.py --symbol BTCUSDT --debug

  3. Balance Insufficient

    # Check account balance
python balance.py

Error Codes

  • -1001: Invalid symbol
  • -1003: Too many requests
  • -1013: Invalid quantity
  • -2010: Account has insufficient balance

⚠️ Disclaimer

🚨 Important Legal Notice

This software is for educational and research purposes only. Trading cryptocurrencies involves substantial risk of loss and is not suitable for all investors. The high degree of leverage can work against you as well as for you.

Risk Warnings

  • Market Risk: Cryptocurrency markets are highly volatile
  • Technical Risk: Software bugs may cause unexpected losses
  • Regulatory Risk: Trading regulations may change
  • Liquidity Risk: Some assets may have limited liquidity

No Financial Advice

  • This bot does not provide financial advice
  • All trading decisions are your responsibility
  • Past performance does not guarantee future results
  • Always do your own research before trading

Use at Your Own Risk

  • No warranties or guarantees are provided
  • No liability for any losses incurred
  • Test thoroughly before using real funds
  • Start small and scale gradually

📄 License

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

MIT License Summary

  • ✅ Commercial use allowed
  • ✅ Modification allowed
  • ✅ Distribution allowed
  • ✅ Private use allowed
  • ❌ No liability or warranty provided

🚀 Ready to Start Trading?

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