🚀 Professional Crypto Backtesting System v3.0

Features

✅ What's New

• Modular Strategy System - Each strategy in its own file
• Leverage Support - 1x to 125x leverage
• Risk Management - Control position size (% of account per trade)
• Stop Loss & Take Profit - Automatic risk controls
• Professional Strategies - Advanced indicators and logic
• Easy to Extend - Just drop new strategy files in the folder

📁 File Structure

backtest_pro.py              # Main GUI application
strategies/
├── base_strategy.py         # Base class (inherit from this)
├── sma_strategy.py          # SMA Crossover
├── rsi_strategy.py          # RSI with dynamic levels
├── macd_strategy.py         # MACD with histogram
├── bollinger_strategy.py    # Bollinger Bands with squeeze
├── scalping_strategy.py     # High-frequency scalping
└── grid_strategy.py         # Grid trading for ranges

🚀 Quick Start

python backtest_pro.py

💡 Key Features

Leverage & Risk Management

• Leverage: 1x to 125x (like real exchanges)
• Risk per Trade: Default 2% (adjustable)
• Stop Loss: Automatic stop at X%
• Take Profit: Automatic profit taking

Example Settings

• Conservative: 1-3x leverage, 1-2% risk
• Moderate: 5-10x leverage, 2-3% risk
• Aggressive: 20-50x leverage, 3-5% risk
• Degen: 100-125x leverage, 5-10% risk

📝 Adding New Strategies

Step 1: Create a new file in strategies/ folder

# strategies/my_strategy.py

from base_strategy import BaseStrategy
import backtrader as bt

class MyStrategy(BaseStrategy):
    
    strategy_name = "My Custom Strategy"  # This appears in dropdown
    
    params = (
        # Add your custom parameters here
        ('my_param', 20),
        # Keep these for risk management
        ('printlog', False),
        ('risk_per_trade', 2.0),
        ('leverage', 1),
        ('stop_loss_pct', 2.0),
        ('take_profit_pct', 6.0),
        ('use_risk_management', True),
    )
    
    def __init__(self):
        super().__init__()
        # Initialize your indicators here
        self.sma = bt.indicators.SMA(self.dataclose, period=self.params.my_param)
    
    def buy_signal(self):
        # Return True when you want to buy
        return self.dataclose[0] > self.sma[0]
    
    def sell_signal(self):
        # Return True when you want to sell
        return self.dataclose[0] < self.sma[0]

Step 2: Click "Reload Strategies" in the GUI

That's it! Your strategy appears in the dropdown.

🎯 Strategy Descriptions

SMA Crossover

• Classic moving average crossover
• Best for: Trending markets
• Timeframes: 1h, 4h, 1d

RSI Dynamic

• RSI with dynamic exit levels
• Best for: Ranging markets
• Timeframes: 15m, 30m, 1h

MACD Advanced

• MACD with histogram confirmation
• Best for: Momentum trading
• Timeframes: 30m, 1h, 4h

Bollinger Bands Pro

• Mean reversion with squeeze detection
• Best for: Volatile markets
• Timeframes: 15m, 1h, 4h

Scalper Pro

• High-frequency with tight stops
• Best for: 1m, 5m charts
• Use 10-20x leverage

Grid Trading

• Automated grid with dynamic levels
• Best for: Sideways markets
• Timeframes: 5m, 15m, 30m

⚙️ Recommended Settings

For Scalping (1m-5m)

Strategy: Scalper Pro
Leverage: 10-20x
Risk per Trade: 1%
Stop Loss: 0.5%
Take Profit: 1%

For Day Trading (15m-1h)

Strategy: RSI Dynamic / MACD
Leverage: 5-10x
Risk per Trade: 2%
Stop Loss: 2%
Take Profit: 4-6%

For Swing Trading (4h-1d)

Strategy: SMA Crossover / MACD
Leverage: 2-5x
Risk per Trade: 2-3%
Stop Loss: 3%
Take Profit: 10%

📊 Understanding Results

With Leverage

• 10x leverage + 10% gain = 100% profit
• 10x leverage + 10% loss = 100% loss
• Higher leverage = higher risk/reward

Risk Management

• 2% risk = Maximum 50 trades to blow account
• 5% risk = Maximum 20 trades to blow account
• Always use stop losses with leverage!

🔥 Pro Tips

1. Start with low leverage (1-5x) until profitable
2. Backtest all timeframes to find the best
3. Use risk management - Never risk more than 5%
4. Different strategies for different markets:
   • Trending → SMA, MACD
   • Ranging → RSI, Bollinger, Grid
   • Volatile → Scalper
5. Combine strategies - Use different strategies for different pairs

⚠️ Warnings

• Leverage amplifies losses - 10x leverage means 10x losses too
• Past performance ≠ future results
• Test on paper trading first
• Never trade money you can't afford to lose

🐛 Troubleshooting

"No strategies loaded"

• Check the strategies/ folder exists
• Ensure strategy files have strategy_name attribute
• Click "Reload Strategies" button

"No trades executed"

• Strategy signals too restrictive
• Try different timeframes
• Adjust strategy parameters

GUI not opening

pip install tkinter pandas numpy backtrader ccxt matplotlib

📈 Example Results

With proper settings you should see:

• Win Rate: 40-60% (typical)
• Total Return: Varies greatly with leverage
• Sharpe Ratio: > 1.5 (good)
• Max Drawdown: < 20% (with risk management)

🚀 Getting Started

1. Run: python backtest_pro.py
2. Select a strategy
3. Set leverage (start with 1-5x)
4. Set risk per trade (2%)
5. Click "Test All Timeframes"
6. Find best performing setup
7. Create your own strategies!

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Remember: This is for backtesting only. Real trading involves real risk!