Proteus Actuarial Library Documentation

Welcome to the Proteus Actuarial Library (PAL) documentation!

PAL is a fast, lightweight framework for building simulation-based actuarial and financial models. It handles complex statistical dependencies using copulas while providing simple, intuitive syntax.

Key Features:

  • Built on NumPy/SciPy for performance

  • Optional GPU acceleration with CuPy

  • Automatic dependency tracking between variables

  • Comprehensive statistical distributions

  • Clean, Pythonic API

Quick Start

from pal import distributions, copulas

# Create stochastic variables
losses = distributions.Gamma(alpha=2.5, theta=2).generate()
expenses = distributions.LogNormal(mu=1, sigma=0.5).generate()

# Apply statistical dependencies
copulas.GumbelCopula(theta=1.2).apply([losses, expenses])

# Variables are now correlated
total = losses + expenses

Installation

# Basic installation
pip install proteusllp-actuarial-library

# With GPU support
pip install proteusllp-actuarial-library[gpu]

Additional Information

Indices and tables