quantbullet is a toolkit designed for streamlined quantitative analysis in finance. The goals for this package are:
- To provide a practical set of tools for prototyping quantitative research ideas.
- To integrate and test contemporary research findings, primarily from academic sources, ensuring they're actionable.
While I initially developed this package for my own needs, I intend to maintain it consistently. If it assists others in their endeavors, I consider that a success.
$ pip install quantbullet- Statistical Jump Models. See this notebook for an example. Statistical jump models are a type of regime-switching model that applies clustering algorithms to temporal financial data, explicitly penalizing jumps between different financial regimes to capture true persistence in underlying regime-switching processes.
Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.
quantbullet was created by Yiming Zhang. It is licensed under the terms of the MIT license.
This project developement is generously supported by JetBrains softwares with their Open Source development license.
quantbullet was created with cookiecutter and the py-pkgs-cookiecutter template. Python Packages is an excellent resource for learning how to create and publish Python packages.