Stochastic Processes Python Packages

torchsde

Differentiable SDE solvers with GPU support and efficient sensitivity analysis.

gpflow

Gaussian processes in TensorFlow

stochastic

Generate realizations of stochastic processes in python.

lspopt

Python implementation of a multitaper window method for estimating Wigner spectra for certain locally stationary processes

stochastic-rs

High-performance quantitative finance in Rust — 120+ stochastic processes, option pricing, calibration, fixed income, risk & copulas, with SIMD/GPU acceleration and Python bindings.

pysteps

Python framework for short-term ensemble prediction systems.

mfdfa

Multifractal Detrended Fluctuation Analysis in Python

fvgp

A software package for flexible HPC GPs

sde-sim-rs

Powerful and flexible stochastic differential equation (quasi) Monte-Carlo simulation library written in Rust with Python bindings

tme

Taylor moment expansion in Python

stochvolmodels

Python implementation of pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, Heston

pycurve

PyCurve : Python Yield Curve is a package created in order to interpolate yield curve, create parameterized curve and create stochastic simulation.

humantyping

The most realistic keyboard typing simulator based on Markov Chains. Models authentic human behavior (errors, corrections, fatigue, speed variations) for Playwright and Selenium automation.

quantflow

Quantitative finance and derivative pricing

aleatory

📦 Python library for Stochastic Processes Simulation and Visualisation

easy-tpp

EasyTPP: Towards Open Benchmarking Temporal Point Processes

sdepy

SdePy: Numerical Integration of Ito Stochastic Differential Equations

finstoch

FinStoch is a Python library designed to model and analyze stochastic processes commonly used in financial applications. The library includes tools for simulating, visualizing, and applying stochastic models such as Geometric Brownian Motion, Merton's Jump-Diffusion, and Heston's model, etc.

gansforvirtualeye

This package provides an implementation of Generative Adversarial Networks (GANs) for time series generation, with flexible architecture options. Users can select different combinations of generator and discriminator models, including Convolutional Neural Networks (CNN) and Long Short-Term Memory networks (LSTM), to suit their specific needs.

derivatives-pricing

A Python library for options pricing and Greeks computation.

ergodicity

A comprehensive toolkit for ergodicity economics and related fields.

ethz-snow

A Python package describing Stochastic Nucleation of Water in vials

pyrandwalk

:walking:Python Library for Random Walks

pyesg

Economic scenario generator for python: simulate stocks, interest rates, and other stochastic processes.