This options pricing framework is made for experimentation and learning.

Option Pricing Framework

A comprehensive Python framework for pricing financial options using various models and simulation techniques.

Features

Multiple option pricing models:

• Black-Scholes
• Binomial
• Monte Carlo simulation
• Least Squares Monte Carlo for American options
• Analytical and simulated Asian options

Flexible simulation models:

• Geometric Brownian Motion
• Generic Drift-Diffusion Process
• Heston Stochastic Volatility
• Ornstein-Uhlenbeck Process

Support for different option types:

• European options
• American options
• Asian options

Volatility models:

• GARCH

Utility functions:

• Implied volatility calculation
• Historical data analysis
• Distribution fitting

Installation

git clone https://github.com/yourusername/option_pricing_framework.git
cd option_pricing_framework
pip install -r requirements.txt

Usage

Here's a basic example of pricing a European call option using the Black-Scholes model:

from models.european.black_scholes import BlackScholesModel

params = {
    'initial_stock_price': 100,
    'strike_price': 100,
    'time_to_maturity': 1,
    'risk_free_rate': 0.05,
    'volatility': 0.2,
    'option_type': 'call'
}

bs_model = BlackScholesModel()
price = bs_model.price(params)
print(f"Option price: {price}")

Project Structure

• models/: Contains various option pricing models
• simulations/: Implements different simulation techniques
• distributions/: Defines probability distributions used in simulations
• utils/: Utility functions for data analysis and calculations
• experiments/: Jupyter notebooks demonstrating various pricing scenarios
• tests/: Unit tests for the framework components

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License.

Acknowledgements

This framework was inspired by and built upon various financial engineering concepts and techniques. Special thanks to all the researchers and practitioners in the field of quantitative finance.