Quick Start

1
Choose between Block or Code mode
2
Select your stock and date range
3
Build your strategy using blocks or write code directly
4
Run your backtest to see results

Working Modes

Block Mode

Visual programming interface for building strategies using drag-and-drop blocks. Perfect for beginners or rapid prototyping.

Try Block Mode

Code Mode

Write Python code directly with full access to pandas, numpy, and backtesting libraries. Ideal for advanced users.

Try Code Mode

API Reference

Available Libraries

pandas

Data manipulation and analysis

numpy

Scientific computing and numerical operations

backtesting

Strategy testing and optimization

Example Strategies

Simple Moving Average Crossover

class SMAStrategy(Strategy):
    n1 = 10  # Fast SMA
    n2 = 20  # Slow SMA
    
    def init(self):
        self.sma1 = self.I(SMA, self.data.Close, self.n1)
        self.sma2 = self.I(SMA, self.data.Close, self.n2)
    
    def next(self):
        if crossover(self.sma1, self.sma2):
            self.buy()
        elif crossover(self.sma2, self.sma1):
            self.sell()

Try This Example

Platform Features

Visual Programming

Our visual programming interface allows you to build trading strategies without writing code.

✓Access the Block Mode in the playground
✓Drag and drop blocks to create your strategy logic
✓Connect blocks to create trading conditions
✓Use built-in indicators and technical analysis tools
✓Test your strategy with real market data

Intuitive Code Editor

Our code editor is designed for efficient strategy development with features including:

✓Syntax highlighting for Python
✓Real-time error checking
✓Auto-completion for common trading functions
✓Integrated documentation
✓Code formatting and linting

Advanced Backtesting

Our backtesting engine provides comprehensive analysis of your trading strategies:

✓High-performance historical data processing
✓Detailed performance metrics (Sharpe ratio, drawdown, etc.)
✓Interactive charts and visualizations
✓Trade-by-trade analysis
✓Position sizing and risk management tools

Python Ecosystem

Leverage the power of Python's data science stack:

✓Pandas for data manipulation and analysis
✓NumPy for numerical computations
✓Built-in technical analysis libraries
✓Custom indicator development
✓Integration with popular ML frameworks

Ready to Start Building Your Trading Strategy?

Join the growing community of traders using BacktestBull to build, test, and perfect their trading algorithms.

Start Building Now

BacktestBull Documentation