Dev/Creator

tubakhxn

Project Overview

This is a modular Python backtesting engine for evaluating trading strategies on historical financial data. It supports plug-and-play strategies, realistic trade simulation, and comprehensive performance metrics and visualizations.

Features

• Load historical price data (CSV or Yahoo Finance)
• Modular strategy system (easily add new strategies)
• Built-in strategies: Moving Average Crossover, Mean Reversion (z-score)
• Simulate trades with transaction costs
• Track portfolio value and performance
• Metrics: Total Return, Sharpe Ratio, Max Drawdown, Win Rate
• Visualizations: Price with signals, Equity curve, Drawdown

How to Fork and Use

1. Fork this repository on GitHub (or download the code).
2. Install dependencies:

   pip install -r requirements.txt
   # or manually:
   pip install pandas numpy matplotlib yfinance

3. Run main.py to start backtesting with default settings.
4. Modify or add strategies in the strategies/ folder.
5. Use your own data by editing main.py to load a CSV or change the ticker.

Relevant Wikipedia Links

• Backtesting
• Moving Average
• Mean Reversion
• Sharpe Ratio
• Drawdown (economics)