High-frequency statistical arbitrage

Python code of commonly used stochastic models for Monte-Carlo simulations

🦀 Scientific Computing Benchmark: Rust 🦀 vs Zig ⚡ vs the father C 👴

Hamiltonian Monte Carlo (HMC) sampling method in Python3, based on the original paper: Simon Duane, Anthony D. Kennedy, Brian J. Pendleton and Duncan Roweth (1987). "Hybrid Monte Carlo". Physics Letters B. 195 (2): 216–222.

Variational quantum simulations of stochastic differential equations

Ornstein unlenbeck process simulation in python

Python simulations for CTRWs Ornstein-Uhlenbeck process with different stability index

Mean Reversion Trend Analysis with the Ornstein–Uhlenbeck Model

Stochastic Differential Equations and Temperature — NASA Climate Data pt. 2 The Ornstein-Uhlenbeck process in Python

Verification of a quantitative trading strategy using bootstrap OU calibration and backtesting.

Stochastic Processes: Basic Examples

Synthetic Data Generation

A Pyro-PPL implementation of a 2D Ornstein-Uhlenbeck process using stochastic variational inference.

This repository contains some codes simulating diffusion procceses whose diffusion coefficient has stochastic nature. In particular in the Diffusing diffusivity case the diffusion coefficient is distributed according to the Ornstein-Uhlenbeck process while the Dice Brownian is a Random Walk where the step length varies randomly.

A high-performance, event-driven backtesting engine designed for the modern web. Built with PyScript and Python, this engine runs entirely in your browser - no backend servers or complex local environments required.

Solve the Inverted Pendulum Control problem using Deep Deterministic Policy Gradient model

Implementation of a Denoising Diffusion Probabilistic Model with some mathematical background.

An illustration of a stock-trading algorithm using the Ornstein-Uhlenbeck stochastic process.

Numerical investigation of vortex acoustic lock-in in combustors of gas turbine engines under the influence of turbulent flow fields