PortfolioAnalytics.jl
Tool for Quantitative Portfolio Analytics
The PortfolioAnalytics.jl aims to provide users with functionality for performing quantitative portfolio analytics. The package is under heavy development, and new functionalities will be added as part of ongoing releases.
The following functions are available in stable version:
- asset_return( )
- portfolio_return( )
- sharpe( )
- value_at_risk( )
- portfolio_optimize( )
- mean_returns( )
- stddev( )
- moments( )
- es( )
- cumulative_return( )
- drawdowns( )
This package generally requires return (rather than price) data. Almost all functions will work with any periodicity, from annual, monthly, daily, to even minutes and seconds, either regular or irregular.
Getting started
- The best place to get started with PortfolioAnalytics is the Tutorials section, where you can find the demonstration of functions' use.
- Go to the Installation guide to learn how you can install PortfolioAnalytics.
- Read the Functions section to learn more about functions' parameters and default arguments.
Contributions are most welcome
We greatly value contributions of any kind. Contributions could include but are not limited to documentation improvements, bug reports, new or improved code, scientific and technical code reviews, infrastructure improvements, mailing lists, chat participation, community help/building, education, and outreach.
Bug reports and feature requests
Please report any issues via the GitHub issue tracker. All kinds of issues are welcome and encouraged; this includes bug reports, documentation typos, feature requests, etc.
Acknowledgement
The package is inspired by PerformanceAnalytics and PortfolioAnalytics packages in R and pyfolio in Python.