🚀 CEX Option Futures Stock Quant Algorithm Trading Bot

Advanced Algorithmic Trading Bot for Centralized Exchanges

📋 Table of Contents

🌟 Features
🏢 Supported Exchanges
⚡ Trading Algorithms
🚀 Quick Start
📖 Installation
⚙️ Configuration
💡 Usage Examples
📊 Advanced Features
🐳 Docker Support
📈 Performance Monitoring
🔧 API Documentation
🤝 Contributing
📞 Support & Contact
⚠️ Disclaimer
📄 License

🌟 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

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
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

General Support: aostrega822@gmail.com
Technical Issues: aostrega822@gmail.com
Business Inquiries: aostrega822@gmail.com

📋 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

API Connection Errors

# Check API credentials
python test_connection.py

Order Execution Failures

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

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?

Made with ❤️ by the Trading Bot Community

Name		Name	Last commit message	Last commit date
Latest commit History 1,114 Commits
app		app
db		db
.dockerignore		.dockerignore
.gitignore		.gitignore
Dockerfile		Dockerfile
README.md		README.md
balance.py		balance.py
trader.py		trader.py

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