A Python library for options pricing and Greeks computation.

📈 Apply financial engineering techniques to option pricing using Monte Carlo simulations and the Black-Scholes model with clear, documented Python code.

Pricing models for different types of option contracts.

Physics-informed Fourier Neural Operator (FNO) framework for fast pricing and Greeks computation of barrier options under Black–Scholes PDE, developed for an MSc thesis.

SSRN working paper and reproducibility package for barrier option pricing with structurally constrained PINNs and FDM benchmarks.

An advanced Python framework for pricing financial derivatives beyond Black-Scholes using the Heston Stochastic Volatility Model and the Merton Jump Diffusion Model. The project evaluates European, American, and Barrier options, analyzes strike sensitivities, and computes Greeks using Monte Carlo simulations.

Pricing crypto prediction markets (Polymarket) as one-touch barrier options against the Deribit vol surface.

Extension of the Black-Scholes framework to path-dependent derivatives (Barrier Options) using stochastic calculus, the reflection principle, and PDE replication.

Option Pricing with Monte Carlo Simulation — A Python library implementing Black–Scholes analytic pricing, Monte Carlo simulations (with variance reduction, quasi-MC), and advanced derivatives such as Asian, Barrier, and American options. Includes performance acceleration using Numba and comprehensive documentation with visualizations.

A modular Python project for computational finance and stochastic modelling.

MATLAB implementation of European, Barrier (Up&Out), and Bermudan option pricing via CRR Binomial Trees and Monte Carlo simulations. Includes Greeks (Delta, Vega), convergence analysis, and variance reduction via antithetic variables.