Markowitz | First Attempt at Markowitz portfolio optimization | Portfolio library

by mopugh Python Version: Current License: No License

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

kandi X-RAY | Markowitz Summary

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

First Attempt at Markowitz portfolio optimization Must have CVXOPT package installed.

Support

Quality

Security

License

Reuse

Support

Markowitz has a low active ecosystem.

It has 5 star(s) with 2 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

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

It has a neutral sentiment in the developer community.

The latest version of Markowitz is current.

Quality

Markowitz has 0 bugs and 0 code smells.

Security

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

Markowitz code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Markowitz 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

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

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

It has 341 lines of code, 1 functions and 7 files.

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

Top functions reviewed by kandi - BETA

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

Compute the Markowitz Optimization algorithm

Get all kandi verified functions for this library.

Markowitz Key Features

No Key Features are available at this moment for Markowitz.

Markowitz Examples and Code Snippets

No Code Snippets are available at this moment for Markowitz.

Community Discussions

Trending Discussions on Markowitz

Cmake does not see OpenCL

How to speed up cplex solution pool?

QUESTION

Cmake does not see OpenCL

Asked 2022-Mar-17 at 15:32

I am trying to install OpenCL for BEAGLE. First, I have downloaded intel_sdk_for_opencl_applications_2020.3.494.tar.gz from here. Then I unzipped it & run install.sh. Installation was successful. I have BEAGLE installed so I have decided to go to build folder in beagle-lib & run cmake -DCMAKE_INSTALL_PREFIX:PATH=$HOME .. in order to go on to run make install but I get the next message:

...

ANSWER

Answered 2022-Mar-17 at 14:59

Could NOT find OpenCL (missing: OpenCL_LIBRARY OpenCL_INCLUDE_DIR)

Source https://stackoverflow.com/questions/71511678

QUESTION

How to speed up cplex solution pool?

Asked 2020-Jun-08 at 06:52

I have a MIP model that I need to generate its solution pool. Generating this pool takes around 5 minutes but I need to do this pool generation for 100k model, so I need this pool to run at least 8 times faster but unfortunately I don't have any knowledge about speeding up cplex. Is there any settings that I can change in order to make it run faster?Is it possible to make it run in parallel on different CPUs? My pool settings :

...

ANSWER

Answered 2020-Jun-08 at 06:52

Two things come to mind:

Try playing with the MIP emphasis parameter (see here). In particular, try value "4 Emphasize finding hidden feasible solutions". You can also try to crank up heuristics.
If you have more than one core on your machine, then by default CPLEX will use all available cores for solving a model. Instead of throwing all the computing power at one single model you could try to solve several models in parallel, each with a reduced number of threads. For example, if you have 12 cores then you can either solve one model with 12 models or you can solve 4 models in parallel, using 3 threads for each. Depending on how well CPLEX can utilize multiple threads for your instances, the latter approach may be faster.

Source https://stackoverflow.com/questions/62216786

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

Vulnerabilities

No vulnerabilities reported

Install Markowitz

You can download it from GitHub.
You can use Markowitz 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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