Collection of notebooks about quantitative finance, with interactive python code.

High-frequency statistical arbitrage

A statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.

A library of noise processes for stochastic systems like stochastic differential equations (SDEs) and other systems that are present in scientific machine learning (SciML)

Black Scholes Option Pricing calculator with Greeks and implied volatility computations. Geometric Brownian Motion simulator with payoff value diagram and volatility smile plots. Java GUI.

An R Package for Monte Carlo Option Pricing Algorithm for Jump Diffusion Models with Correlational Companies

Lorenz attractors, statistical mechanics, nonlinear dynamical systems, computational physics.

A python code to calculate the Brownian motion of colloidal particles in a time varying force field.

Fast and slight DLA3D / DLA2D (Diffusion Limited Aggregation)

Case Studies in Finance: Stock Price Valuation using Black-Scholes using Brownian Motions, Investment Project comparing Stocks and Bonds, Determining Pension Fund's Premium. (Case Study Papers and Code)

A UI-friendly program calculating Black-Scholes options pricing with advanced algorithms incorporating option Greeks, IV, Heston model, etc. Reads input from users, files, databases, and real-time, external market feeds (e.g. APIs).

Ornstein-Uhlenbeck models for phylogenetic comparative hypotheses

Python solver for the Brownian, Stochastic, or Noisy Differential Equations

Resources for Quantitative Finance

CAAStools is a bioinformatics toolbox that allows the user to identify and validate CAAS on MSA of orthologous proteins.

Research and programming of various interesting mathematical examples

Simulation of Langevin dynamics

Oldschool PlasmaFractal revival with Perlin Noise and WebGL

Project funded by DFG. A jupyter-book that explores mearly a chunk of the field of nonlinear dynamics, specifically diffusion and random search in heterogeneous media. The book has various simulations for the stochastic process known as Brownian motion. The motion dynamics are simulated by solving the Langevin equation numerically for the differ…

Stochastic processes insights from VAE. Code for the paper: Learning minimal representations of stochastic processes with variational autoencoders.