chainladder (python)
chainladder - Property and Casualty Loss Reserving in Python
This package gets inpiration from the popular R ChainLadder package.
This package strives to be minimalistic in needing its own API. Think in pandas for data manipulation and scikit-learn for model construction. An actuary already versed in these tools will pick up this package with ease. Save your mental energy for actuarial work.
Available Estimators
chainladder has an ever growing list of estimators:
| Loss Development | Tails Factors | IBNR Models | Adjustments & Workflow |
|---|---|---|---|
| Development | TailCurve | Chainladder | BootstrapODPSample |
| DevelopmentConstant | TailConstant | MackChainladder | BerquistSherman |
| MunichAdjustment | TailBondy | BornhuettterFerguson | Pipeline |
| ClarkLDF | TailClark | Benktander | GridSearch |
| IncrementalAdditive | CapeCod |
Documentation
Please visit the Documentation page for examples, how-tos, and source code documentation.
Getting Started Tutorials
Tutorial notebooks are available for download here.
- Working with Triangles
- Selecting Development Patterns
- Extending Development Patterns with Tails
- Applying Deterministic Methods
- Applying Stochastic Methods
- Large Datasets
Installation
To install using pip:
pip install chainladder
Alternatively, install directly from github:
pip install git+https://github.com/casact/chainladder-python/
Note: This package requires Python 3.5 and later, numpy 1.12.0 and later, pandas 0.23.0 and later, scikit-learn 0.18.0 and later.
Questions?
Feel free to reach out on Gitter.
Want to contribute?
Check out our contributing guidelines.