my_package_project 1.3.0

A package that I created for my Python project :)

my_package_project

A package that I created for my Python project :)

Installation

$ pip install my_package_project

Usage

• This package is an extenstion of the pybacktestchain package.

• This package is designed to provide tools for backtesting financial strategies, with a focus on risk parity portfolios.

• It enables to evaluate portfolio performance through various metrics, including portfolio volatility, annaulized return, risk contributions or Sharpe ratio.

• It also includes functionality to visualize portfolio characteristics and performance over time.

• Output and Reporting:

  • Generates interactive visualizations.
  • Exports results as a Jupyter Notebook for detailed review.
  • Saves plots and transaction logs for further analysis.

Example of usage

from datetime import date, timedelta, datetime
from my_package_project.data_treatment import *
from my_package_project.graphs  import *
from my_package_project.operations import *

test = Backtest_up(
    initial_date = datetime(2017, 1, 1),
    final_date = datetime(2020, 12, 31),
    information_class = FirstTwoMoments,
    risk_model=StopLoss,
)
test.run_backtest()

Key classes and functions

Backtest Framework: (operations)

• Backtest_up:
  • Runs the backtest, calculates metrics, and generates reports.

Portfolio Visualizations: (graphs)

• PortfolioVisualizer:
  • Visualizes initial portfolio weights and risk contributions.
  • Methods:
    • plot_portfolio_weights: Bar chart of portfolio weights.
    • plot_risk_allocation_pie: Pie chart of risk contributions.
• PortfolioVisualizer_over_time:
  • Tracks portfolio performance and weights over time.
  • Methods:
    • plot_portfolio_weights_over_time: Stacked area chart of weights.
    • plot_portfolio_value_over_time: Line chart of portfolio value.
    • compute_annualized_returns: Calculates portfolio annualized returns.
    • compute_annualized_volatility: Calculates portfolio annualized volatility.
    • compute_sharpe_ratio: Calculates the Sharpe ratio.

Risk Parity Framework: (data_treatment)

• compute_risk_contributions: Computes the contribution of each asset to portfolio risk.
• portfolio_volatility: Calculates portfolio volatility using covariance matrix.
• RiskParity:
  • compute_portfolio_riskparity: Constructs risk parity portfolio.
  • compute_portfolio_riskparity_voltarget_leverage : Constructs risk parity portfolios with optional leverage and target volatility.

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

my_package_project was created by marcdeslis. It is licensed under the terms of the MIT license.

Credits

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