bond_pricing | Bond pricing using YTM or zero curve

by jrvarma Python Version: Current License: GPL-3.0

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

kandi X-RAY | bond_pricing Summary

bond_pricing is a Python library. bond_pricing has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can install using 'pip install bond_pricing' or download it from GitHub, PyPI.

This package provides bond pricing functions as well as basic NPV/IRR functions. Bond valuation can be done using an yield to maturity or using a zero yield curve. There is a convenience function to construct a zero yield curve from a few points on the par bond or zero yield curve or from Nelson Siegel parameters. The documentation is available at

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Quality

Security

License

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Support

bond_pricing has a low active ecosystem.

It has 7 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 1 have been closed. On average issues are closed in 2 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of bond_pricing is current.

Quality

bond_pricing has 0 bugs and 0 code smells.

Security

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

bond_pricing code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

bond_pricing is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

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

Deployable package is available in PyPI.

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

It has 757 lines of code, 56 functions and 9 files.

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

Top functions reviewed by kandi - BETA

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

Calculates an annuity breakup
Variant of FVF
R Calculates the equivance of two frequencies
Calculate an annuity frequency rate
Creates a key - value - shifted key - value curve
Interpolate x r
Calculate key rate shift
Create a function that returns a function that returns a zero price function
Find the root of f
Find bracket root
Implement bisection
Creates a Zero Spread
Calculates the bond price for a given bracket price
Bond price breakdown
Calculate the bond duration of a ZeroCurve
Calculate the duration of a frequency domain
Calculate the irr coefficient
Calculate a frequency domain waveform
Return a list of coupon periods for a given settle
Evaluate a time series
Computes the duration of a bond
Returns a pandas dataframe with bondon periods
Calculate annuity periods
Create a DataFrame of key - value pairs
Imports the standard daycounters
Wrapper around bond yield

Get all kandi verified functions for this library.

bond_pricing Key Features

No Key Features are available at this moment for bond_pricing.

bond_pricing Examples and Code Snippets

No Code Snippets are available at this moment for bond_pricing.

Community Discussions

No Community Discussions are available at this moment for bond_pricing.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install bond_pricing

You can install using 'pip install bond_pricing' or download it from GitHub, PyPI.
You can use bond_pricing 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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