Pytorch implementation of OCFGAN-GP (CVPR 2020, Oral).

📚SDE research and modelling in Finance📚

A repo which deals with Computational Methods in Mathematics, mainly applied in the context of Mathematical Finance, even though it can be applied to almost any domain where you need Probability, Partial Differential Equations, Stochastic Differential Equations, Characteristic Functions, Lévy Processes, Stochastic Volatility, FFT, etc.

This project aims to implement the Heston model (1993) and apply it to price Equity Variance & Volatility Swaps.

High-performance Python engine implements Fourier-based option pricing, volatility surface calibration, and risk analytics. It features six stochastic models—including Heston and CGMY—ensuring martingale consistency. Utilizing Carr-Madan FFT and COS methods, it delivers precise Greeks and VaR/CVaR metrics.

Python package for characteristic functions inversion

This Matlab function performs the numerical inversion of a symbolic expression representing a Characteristic function of a discrete distribution, and outputs the discrete CDF over a custom range.

R package for estimation of the four parameters of stable distributions. The package also provides functions to compute characteristic functions and tools to run Monte Carlo simulations.