pybacktestchain-ev 0.1.0

Improved pybacktestchain library with interactive UI and features added (risk measures, trading strategies, multiple asset classes)

pybacktestchain_EV

Package for the Python Course based on pybacktestchain library by J. Imbett.

Overview

pybacktestchain_EV is a Python package designed to facilitate portfolio backtesting using various trading strategies. The package incorporates risk management tools, blockchain-based backtest storage, and a user-friendly interface built with Streamlit.

Installation

You can install the package via pip:

$ pip install pybacktestchain_EV

Features

• Interactive UI: A Streamlit-based interactive interface for configuring backtests, visualizing results, analyzing performance and risk metrics.
• Portfolio Backtesting: Supports backtesting of standard trading strategies such as Equal Weight, Minimum Variance, Maximum Sharpe Ratio, and Risk Parity.
• Customizable Transaction Costs: Allows precise configuration of trading fees for realistic simulations.
• Risk Management: Includes stop-loss and take-profit mechanisms with customizable thresholds, as well as Value-at-Risk (VaR) and Expected Shortfall for the backtested portfolio.
• Blockchain Integration: Stores backtest results in a blockchain.

Usage

Running the Streamlit Interface

To start the Streamlit interface:

$ streamlit run <your_app_file>.py

Configuring a Backtest

1. Select Tickers: Enter stock tickers (comma-separated) to define the universe (works across all asset classes).
2. Set Parameters:
   • Initial cash amount.
   • Start and end dates for the backtest.
   • Choose a strategy: Equal Weight, Minimum Variance, Maximum Sharpe Ratio, or Risk Parity.
   • Configure risk management: Stop-loss, take-profit percentages, and transaction costs.
3. Run the Backtest: Click the "Run Backtest" button.

Viewing Results

• Portfolio value and returns are displayed over time, as well as the distribution of returns.
• Risk metrics, such as Value-at-Risk (VaR) and Expected Shortfall (ES), are calculated.
• A transaction log is provided for detailed insights and store to the blockchain.
• Additional visualizations include correlation heatmaps and return distributions.

Blockchain Storage

Each backtest is saved in a blockchain under a randomly generated name. This ensures results are tamper-proof and can be referenced later. Blockchain files are stored in the blockchain/ directory within the package folder.

Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

License

pybacktestchain_EV was created by Enzo Volpato. It is licensed under the terms of the MIT license.

Credits

pybacktestchain_EV was created with cookiecutter and the py-pkgs-cookiecutter template.