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Description:

cifrum 0.2.6

Status

Examples

Support

cifrum – a flexible and easy-to-use Python 3.6+ library for analysis &
manipulation with financial & economic data
cifrum is released under the terms of GPL license. We appreciate all kinds of
contributions, financial resources to maintain the project and accelerate its
development.
If you find cifrum useful in your financial research, private investments or
company, please consider making a donation to the project commensurate with
your resources. Any amount helps!
All donations will be used strictly to fund cifrum development supporting
activities: the Python library development, frontend solutions,
documentation and maintenance work, and paying for hosting costs of servers.
If you are interested in donating to the project, please, use the Paypal
button:

Contents of this Document

Introduction
Applications
The Ecosystem
Main Features
Financial and Economic data freely available
Installation
Jupyter Notebooks
Dependencies
Discussion, Development, and Getting Help
Contributing
License

Introduction
cifrum is a Python library developed to solve quantitative finance and
investments tasks. Additionally, it has the broader goal to become the most
useful and flexible open sourced tool for financial data analysis available in
popular programming languages.

Applications
Useful applications of cifrum in the community developed are as follows:

Fully-functional Angular2+-based web-application okama.io
tell us more if you know any

The Ecosystem
The ecosystem around the library consists of:

The Python package
Financial and Economic data for several markets
Angular2+ web-application okama.io
Financial terms glossary
The community

Main Features

[x] TimeSeries to verify correctness of financial data manipulations
[x] Error-free manipulations with financial data checked by tests and active community
[x] Asset analysis tools for asset correlations and main performance indicators
[ ] Portfolio analysis tools for asset class allocation and portfolio backtesting
[ ] Portfolio optimization and efficient frontier visualization
[ ] Monte Carlo Simulation for financial assets and investment portfolios
[ ] Bonds key properties calculations
[x] Access to financial data from different stock markets: EOD close, adjusted close, currency rates, inflation
[x] Financial and Economic data with API with GraphQL data access

Financial and Economic data freely available

[x] EOD adjusted close for NYSE and NASDAQ stocks and ETF
[x] EOD close for Moscow Exchange stocks and ETF
[x] EOD close for Russian open-end funds
[ ] EOD close for BSE and NSE stocks and ETF (India)
[x] EOD for main stock and bond Indexes
[ ] Bonds data for Moscow Exchange-traded securities: EOD close, coupons, maturity
[x] Exchange Rates for USD, EUR, RUB
[ ] Exchange Rates for Bitcoin [BTC], Ethereum [ETH], Binance Coin [BNB] and other cryptocurrencies
[x] Inflation for US, EU, and Russia
[x] Key interest rates for US, EU, and Russia
[x] History of deposit rates for top 10 banks of Russia

Installation
The library is published to pypi.org.
Install stable version:
pip install -U cifrum
Install development version:
pip install -U git+https://github.com/okama-io/cifrum.git

Jupyter Notebooks
The examples folder contains Jupyter notebooks
that show how to use the library parts in depth.
examples are also compatible with
binder. You can try it by pressing the button.

Dependencies
The library dependencies are listed at
pyproject.toml under
[tool.poetry.dependencies] section.

Discussion, Development, and Getting Help

The development discussion takes place at the GitHub repo. We encourage you to report issues using the Github
tracker. We welcome all kinds of issues related to
correctness, documentation, performance, and feature requests.
The community forum can also be used for general
questions and discussions.
Finally, the Gitter channel is available for the development
related questions.

Contributing
All contributions, bug reports, bug fixes, documentation improvements,
enhancements, frontend implementation, and ideas are welcomed and the subject
to discuss. Simple ways to start contributing immediately:

Browse the issue tracker to find issues that interest you
Read the source code and improve the documentation or address TODOs
Improve the example library and tutorials
Bug reports are an important part of making the library more stable
Run the library through the okama.io frontend and suggest
improvements in design, UI, and functionality

The code is hosted at GitHub. You need an GitHub account
which is free to contribute to the project. We use git for the version control
to enable distributed work on the project.
Contributions should be submitted as a pull request. A member of the
development team will review the pull request and guide you through the
contributing process.
Feel free to ask questions at the community.

License
GPL