pyfinlab 0.0.7

Financial applications focusing on portfolio management

PyFinanceLab

PyFinanceLab is a project which brings together various financial applications into one package for research and portfolio management. PyFinanceLab is in pre-alpha development. Please open an issue if you find any bugs.

Features

PyFinanceLab is a library of financial applications focusing on portfolio management for Python.

• Data Api Wrapper

  The data api wrapper makes it easy to switch between yfinance (free to use) and tia (Bloomberg Professional Service subscription required) libraries for pulling financial data.

Installation Instructions

Open Anaconda Prompt, navigate to the pyfinlab root directory, and create a new environment.

conda env create -f environment.yml

Activate new environment.

conda activate pyfinlab

Install the latest version using pip.

pip install pyfinlab

Roadmap

Future development will include:

• Classification Schema

  Classify an investment universe of tickers into specified categories such as sector, size, or value.

• Constraints Modeling

  Automatically generate weight constraints for a universe of tickers.

• Risk Modeling

  Sample, test, and select the best risk model for generating covariance matrices for input into portfolio optimizers such as mean-variance optimization (MVO). Examples include empirical covariance, ledoit-wolf shrinkage, minimum covariance determinant, and more.

• Portfolio Optimization

  Utilize the classification schema, constraints modeling, risk modeling, and return modeling to optimize a portfolio of assets.

• Portfolio Backtesting

  Backtest portfolios and generate performance graphical plots and statistics.

• Report Generation

  Report results in a nicely formatted and easily readable Excel file.

• Documentation

  Documentation will be published as this Python library is further developed.