portfolioopt | Financial Portfolio Optimization Routines in Python | Portfolio library

by czielinski Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | portfolioopt Summary

portfolioopt is a Python library typically used in Web Site, Portfolio applications. portfolioopt has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Financial Portfolio Optimization Routines in Python

Support

Quality

Security

License

Reuse

Support

portfolioopt has a low active ecosystem.

It has 270 star(s) with 93 fork(s). There are 34 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 7 have been closed. On average issues are closed in 81 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of portfolioopt is current.

Quality

portfolioopt has 0 bugs and 0 code smells.

Security

portfolioopt has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

portfolioopt code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

portfolioopt is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

portfolioopt releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

portfolioopt saves you 115 person hours of effort in developing the same functionality from scratch.

It has 292 lines of code, 21 functions and 5 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed portfolioopt and discovered the below as its top functions. This is intended to give you an instant insight into portfolioopt implemented functionality, and help decide if they suit your requirements.

Computes a Markowitz portfolio .
Compute the tangency portfolio .
Compute the minimum variance portfolio .
Run test .
r Truncates the weighted weights .
Calculate the maximum return portfolio .
Print information about the portfolio .
Prints a section

Get all kandi verified functions for this library.

portfolioopt Key Features

No Key Features are available at this moment for portfolioopt.

portfolioopt Examples and Code Snippets

No Code Snippets are available at this moment for portfolioopt.

Community Discussions

Trending Discussions on portfolioopt

How to enter console equivalent commands in shiny for interactive functions?

QUESTION

How to enter console equivalent commands in shiny for interactive functions?

Asked 2017-Feb-14 at 21:08

Ok, so i'm sure I worded the question wrong, but is there any way to accomplish the equivalent of entering 1 into the console in Shiny.

Basically I want the following to work in Shiny:

...

ANSWER

Answered 2017-Feb-14 at 21:08

You can use which argument to specify which plots to plot each time:

Source https://stackoverflow.com/questions/42235368

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install portfolioopt

To manually install the library, clone the repository via git clone https://github.com/czielinski/portfolioopt.git and install the module with python setup.py install. To install the requirements by hand you can also use pip install -r requirements.txt. You can run the tests with python setup.py test or with python -m unittest discover in the module directory. If everything is right, all tests should pass. The portfolioopt module provides the optimization routines, the file example.py provides a simple usage example. Please also read the LICENSE.txt file.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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