Life Actuarial Maths
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Updated
Mar 7, 2024 - Julia
Life Actuarial Maths
Tools for creating and working with aggregate probability distributions.
An open-source Python framework for actuarial cash flow models
All Python algorithms published by Open Source Modelling in one place.
Easily Reference and use Actuarial Mortality Tables
Examples and Tutorials using JuliaActuary packages.
A handy tool for actuarial modeling, which is designed to achieve both accuracy and accountability.
Data collection and exploratory analysis related to COVID-19 for general insurance actuaries and the public
Solving Actuarial Math with Python
Classification of reserve risk with chain-ladder
All Matlab algorithms published by Open Source Modelling in one place.
Multi-Population Mortality Modeling With Neural Networks
All JavaScript algorithms published by OSM in one place.
n dimensional Brownian motion with an arbitrary mean and Variance Covariance matrix.
All Jupyter Notebooks implemented by Open Source Modelling in one place.
Black and Sholes model for simulating the stock market in Python.
Validation checks for EIOPA technical submissions written and documented in Jupyter notebooks.
This will house subprojects associated with research papers sponsored by the CAS
In this notebook we take a look at a relevant project that is frequently encountered by insurers: Fraud Detection. For this purpose we use a car data set from a public source and will show the necessary steps to establish an automated fraud detection.
Popular way to model the yield curve called Nelson-Siegel-Svannson algorithm.
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