PyInsurance

A Python library for insurance portfolio management, featuring advanced portfolio protection strategies.

Features

• TIPP Strategy: Time Invariant Portfolio Protection implementation
• High Performance: Cython-optimized core calculations
• Type Safety: Full type hints and static type checking
• Documentation: Comprehensive docstrings and examples

Installation

pip install pyinsurance

For development:

git clone https://github.com/yourusername/pyinsurance.git
cd pyinsurance
pip install -e ".[dev]"

Quick Start

import numpy as np
from pyinsurance.portfolio import TIPP

# Initialize parameters
capital = 100.0
multiplier = 10.0
rr = np.array([0.01, 0.02, -0.01])  # Return rates
rf = np.array([0.001, 0.002, 0.001])  # Risk-free rates
lock_in = 0.05  # 5% lock-in rate
min_risk_req = 0.40  # 40% minimum risk requirement
min_capital_req = 0.80  # 80% minimum capital requirement

# Create TIPP model
tipp = TIPP(
    capital=capital,
    multiplier=multiplier,
    rr=rr,
    rf=rf,
    lock_in=lock_in,
    min_risk_req=min_risk_req,
    min_capital_req=min_capital_req
)

# Run the strategy
tipp.run()

# View results
print(tipp)

Documentation

TIPP Strategy

The Time Invariant Portfolio Protection (TIPP) strategy is designed to protect investment capital while maintaining upside potential. Key features:

• Dynamic floor adjustment
• Capital protection mechanism
• Risk allocation optimization
• Liquidity injection management

API Reference

TIPP Class

class TIPP:
    def __init__(
        self,
        capital: float,
        multiplier: float,
        rr: NDArray[np.float64],
        rf: NDArray[np.float64],
        lock_in: float,
        min_risk_req: float,
        min_capital_req: float,
        freq: float = 252
    ) -> None:
        """Initialize TIPP model with parameters."""

Properties

• portfolio: Current portfolio values
• ref_capital: Reference capital values
• margin_trigger: Margin trigger values
• floor: Floor values
• min_risk_req: Minimum risk requirement
• min_capital_req: Minimum capital requirement
• lock_in: Lock-in rate
• multiplier: Risk multiplier
• rr: Return rate array
• rf: Risk-free rate array

Development

Setup

1. Clone the repository
2. Create a virtual environment
3. Install development dependencies:

   pip install -e ".[dev]"
   

Testing

pytest

Type Checking

mypy .

Code Style

black .
isort .

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests and type checking
5. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Inspired by academic research in portfolio insurance
• Built with Python and Cython
• Uses NumPy for numerical computations