portfolio_optimization | Basic portfolio optimization algorithm | Portfolio library

by kmanley Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | portfolio_optimization Summary

portfolio_optimization is a Python library typically used in Web Site, Portfolio, Example Codes applications. portfolio_optimization has no bugs, it has no vulnerabilities and it has low support. However portfolio_optimization build file is not available. You can download it from GitHub.

Basic portfolio optimization algorithm

Support

Quality

Security

License

Reuse

Support

portfolio_optimization has a low active ecosystem.

It has 9 star(s) with 1 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

portfolio_optimization has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of portfolio_optimization is current.

Quality

portfolio_optimization has no bugs reported.

Security

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

License

portfolio_optimization does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

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

portfolio_optimization has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

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portfolio_optimization Key Features

No Key Features are available at this moment for portfolio_optimization.

portfolio_optimization Examples and Code Snippets

No Code Snippets are available at this moment for portfolio_optimization.

Community Discussions

Trending Discussions on portfolio_optimization

CVXPY Import Error - 'sum_entries' is not defined

Fill an object with the results of every loop iteration in R

QUESTION

CVXPY Import Error - 'sum_entries' is not defined

Asked 2018-Dec-29 at 05:30

I just install the latest version of cvxpy using pip install and am working my way through the examples provided at http://nbviewer.jupyter.org/github/cvxgrp/cvx_short_course/blob/master/applications/portfolio_optimization.ipynb The code does not work for me. When I run the following:

...

ANSWER

Answered 2018-Dec-29 at 05:30

sum_entries was renamed to sum in 1.0.

https://www.cvxpy.org/updates/index.html#numpy-compatibility

Source https://stackoverflow.com/questions/53943840

QUESTION

Fill an object with the results of every loop iteration in R

Asked 2017-Jul-19 at 16:48

first time asker here. I have recently strated working with R and I hope I could get some help with an issue. The problem is probably easy to solve but I haven't been able to find an answer by myself and my research hasn't been succesful either.

Basically I need to create a single object based on the input of a loop. I have 7 simulated asset returns, these objects contain the results from a simulation I ran. I want to match the columns from every object and form a combined one (i.e. every column 1 forms an object), which will be used for some calculations. Finally, the result from each iteration should be stored on a single object that has to be available outside the loop for further analysis.

I have created the following loop, the problem is that only the result from the last iteration is being written in the final object.

...

ANSWER

Answered 2017-Jul-19 at 16:48

By looking at the code, I surmise that the error is in the last line of your for loop.

Source https://stackoverflow.com/questions/45195889

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

Vulnerabilities

No vulnerabilities reported

Install portfolio_optimization

You can download it from GitHub.
You can use portfolio_optimization like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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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