Trading Bot Setup and Usage Guide

📋 Prerequisites

1. Python 3.8+ installed
2. Trading account (Binance, Coinbase, etc.)
3. API credentials from your exchange

🚀 Installation

1. Install dependencies:

pip install -r requirements.txt

2. Configure environment variables: Edit .env file and add your API credentials:

API_KEY=your_binance_api_key
API_SECRET=your_binance_api_secret
EXCHANGE=binance
SYMBOL=BTC/USDT

🎯 Features

1. Multiple Trading Strategies

• Momentum Strategy: RSI + MACD + Price momentum
• Mean Reversion: Bollinger Bands + RSI oversold/overbought
• Breakout Strategy: Volume + Volatility breakouts
• Scalping: High-frequency small profits
• Swing Trading: Longer-term trend following
• Grid Trading: Buy low, sell high in ranges

2. Risk Management

• Position sizing based on Kelly Criterion
• Stop loss and Take profit automation
• Maximum drawdown protection
• Daily loss limits
• Portfolio correlation checks

3. Technical Indicators

• RSI (Relative Strength Index)
• MACD (Moving Average Convergence Divergence)
• Bollinger Bands
• Moving Averages (SMA, EMA)
• Stochastic Oscillator
• Volume indicators

4. Backtesting

• Historical performance analysis
• Performance metrics calculation
• Equity curve visualization
• Risk-adjusted returns

📊 Usage Examples

Basic Usage

from main import TradingBot

# Initialize bot
bot = TradingBot()

# Run strategy once (testing)
bot.run_strategy()

# Start live trading
bot.start_trading()

Advanced Strategy Usage

from strategies import AdvancedStrategies
from main import TradingBot

bot = TradingBot()
strategies = AdvancedStrategies()

# Get data
df = bot.get_historical_data()

# Get signals from multiple strategies
results = strategies.get_strategy_signals(df, [
    'momentum',
    'mean_reversion',
    'breakout'
])

# Aggregate signals
final_signal = strategies.aggregate_signals(results)
print(f"Final signal: {final_signal}")

Backtesting

from backtest import run_backtest

# Run 30-day backtest
metrics = run_backtest()

# Results will show:
# - Total return
# - Win rate
# - Sharpe ratio
# - Maximum drawdown
# - Profit factor

Risk Management

from risk_manager import RiskManager

# Initialize risk manager
risk_manager = RiskManager(initial_balance=1000)

# Calculate position size
position_size = risk_manager.calculate_position_size(
    entry_price=50000,
    stop_loss_price=49000,
    confidence=0.8
)

# Check if can open position
can_trade = risk_manager.can_open_position('long', position_size)

⚙️ Configuration

Environment Variables (.env)

API_KEY=your_api_key
API_SECRET=your_api_secret
EXCHANGE=binance
SYMBOL=BTC/USDT
TIMEFRAME=1m
TRADE_AMOUNT=0.001
STOP_LOSS_PERCENT=2.0
TAKE_PROFIT_PERCENT=3.0

Strategy Parameters (config.py)

RSI_OVERSOLD = 30
RSI_OVERBOUGHT = 70
STOP_LOSS_PERCENT = 2.0
TAKE_PROFIT_PERCENT = 3.0
MAX_RISK_PERCENT = 5.0

🔧 Bot Commands

Testing Mode

python main.py  # Run once for testing

Live Trading Mode

# In main.py, uncomment:
bot.start_trading()

Backtest Mode

python backtest.py

📈 Performance Metrics

The bot tracks:

• Total Return: Overall profit/loss percentage
• Win Rate: Percentage of winning trades
• Sharpe Ratio: Risk-adjusted returns
• Maximum Drawdown: Largest peak-to-trough decline
• Profit Factor: Gross profit / Gross loss
• Average Win/Loss: Average profit per winning/losing trade

🛡️ Risk Management Features

1. Position Sizing: Uses Kelly Criterion for optimal position size
2. Stop Loss: Automatic stop loss at configurable percentage
3. Take Profit: Automatic profit taking at target levels
4. Daily Loss Limit: Stops trading if daily loss exceeds limit
5. Maximum Drawdown: Emergency stop if drawdown too high
6. Correlation Check: Prevents overexposure to correlated positions

📊 Supported Exchanges

• Binance (Primary)
• Coinbase Pro
• Kraken
• Bitfinex
• Huobi

(Add your exchange API credentials in the _init_exchange method)

🚨 Important Notes

1. Paper Trading: Set sandbox=True in exchange config for testing
2. Live Trading: Only use with funds you can afford to lose
3. API Security: Never share your API keys
4. Risk Management: Always use stop losses and position sizing
5. Backtesting: Test strategies thoroughly before live trading

📝 Logging

The bot logs all activities to:

• Console output
• trading_bot.log file

Log levels:

• INFO: General information
• WARNING: Risk warnings
• ERROR: Errors and exceptions
• CRITICAL: Emergency stops

🔍 Monitoring

Monitor your bot through:

• Log files
• Exchange account balance
• Position tracking
• Performance metrics
• Risk status updates

🛠️ Troubleshooting

Common Issues:

1. API Connection: Check API keys and permissions
2. Insufficient Balance: Ensure adequate funds
3. Rate Limits: Bot includes rate limiting
4. Data Issues: Check internet connection and exchange status

Debug Mode:

import logging
logging.basicConfig(level=logging.DEBUG)

📈 Performance Optimization

1. Strategy Combination: Use multiple strategies for better signals
2. Parameter Tuning: Adjust RSI, MACD, and other parameters
3. Timeframe Optimization: Test different timeframes
4. Risk Adjustment: Optimize position sizing and stop losses

🔄 Updates and Maintenance

• Monitor bot performance regularly
• Update strategies based on market conditions
• Adjust risk parameters as needed
• Keep dependencies updated

📞 Support

For issues or questions:

1. Check logs for error messages
2. Review configuration settings
3. Test in sandbox mode first
4. Verify API permissions

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⚠️ DISCLAIMER: Trading cryptocurrencies involves significant risk. This bot is for educational purposes. Always do your own research and never risk more than you can afford to lose.