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Option pricing engine in Python using OOP - supports Black-Scholes, Heston, SABR, Vasicek, and Monte Carlo methods.

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QuantGigi/Multi-Model-Option-Pricing

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Option Pricing Engine (Object-Oriented)

This repository contains a modular and extensible option pricing engine built in Python using an object-oriented approach. The project currently supports multiple stochastic models and pricing methods, focused on vanilla options.

Features

  • Supported Models:

    • Black-Scholes (constant volatility)
    • Heston (stochastic volatility)
    • SABR (stochastic volatility with skew)
    • Vasicek (stochastic interest rates)
  • Pricing Methods:

    • Monte Carlo Simulation
    • Closed-form (when available, e.g. Black-Scholes)
  • Design:

    • Object-oriented structure for clarity and extensibility
    • Easy to plug in additional models
  • Basic unit testing available for key components

  • Ready-to-use Jupyter notebooks for demonstration

Work in Progress

This is not necessarily the final version. The architecture is designed to allow easy integration of new models, methods, or option types (e.g. barrier, Asian, American with LSMC, etc.).

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Option pricing engine in Python using OOP - supports Black-Scholes, Heston, SABR, Vasicek, and Monte Carlo methods.

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