FinQuant | A program for financial portfolio management , analysis

by fmilthaler Python Version: 0.7.0 License: MIT

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

kandi X-RAY | FinQuant Summary

FinQuant is a Python library typically used in Simulation applications. FinQuant has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install FinQuant' or download it from GitHub, PyPI.

FinQuant is a program for financial portfolio management, analysis and optimisation. This README only gives a brief overview of FinQuant. The interested reader should refer to its documentation.

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Quality

Security

License

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Support

FinQuant has a medium active ecosystem.

It has 947 star(s) with 145 fork(s). There are 36 watchers for this library.

There were 9 major release(s) in the last 12 months.

There are 19 open issues and 11 have been closed. On average issues are closed in 16 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of FinQuant is 0.7.0

Quality

FinQuant has 0 bugs and 0 code smells.

Security

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

FinQuant code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

FinQuant 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

FinQuant releases are available to install and integrate.

Deployable package is available in PyPI.

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

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Builds a portfolio
Build a portfolio from a dataframe
Builds a new portfolio from the API
Adds a stock to the portfolio
Compute moving average
Plot Bollinger Band object
Compute moving averages
Return the standard deviation of an ema
Calculate the standard deviation of a rolling window
Computes the minimum volatility
Plot optimal portfolio portfolio
Calculate the minimum volatility
Compute the efficient frontier of the portfolio
Prints a summary of the portfolio
Calculate the coefficient volatility of an objective function
Plot the volatility of the portfolio
Performs a MonteCarlo optimisation
Calculates the EfficientFrontier return weights
Calculates the maximum Sharpe ratio
Calculate the minimum volatility of an EfficientFrontier
Compute the negative Sharpe ratio
Generate random weights for a portfolio
Plot the efficient frontier
Compute the efficient frontier
Emulate ema
Compute the volatility of a portfolio
Compute the mean variance of data
Plot efficiency portfolio
Plots optimal portfolio portfolio

Get all kandi verified functions for this library.

FinQuant Key Features

No Key Features are available at this moment for FinQuant.

FinQuant Examples and Code Snippets

No Code Snippets are available at this moment for FinQuant.

Community Discussions

Trending Discussions on FinQuant

How do I access Quandl web data with FinQuant on Python?

QUESTION

How do I access Quandl web data with FinQuant on Python?

Asked 2019-Nov-22 at 15:10

When trying to access quandl data through the FinQuant package I get an error

...

ANSWER

Answered 2019-Nov-22 at 15:10

I tried downloading stock price data for each of those tickers individually with

Source https://stackoverflow.com/questions/58982162

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

Vulnerabilities

No vulnerabilities reported

Install FinQuant

As it is common for open-source projects, there are several ways to get hold of the code. Choose whichever suits you and your purposes best.

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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