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 👴

Variational quantum simulations of stochastic differential equations

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.

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

Ornstein unlenbeck process simulation in python

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

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.

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

Python library for modelling complex multivariate dependencies using stochastic copulas

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

Synthetic Data Generation

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

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

Stochastic Processes: Basic Examples

Includes generic modules for solving everyday quantitative investment problems. Currently containing simulation and optimization. Aiming to also cover model-fit, data-analysis, metrics.

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

Practical activity for the Physics of Biological Systems minicourse at ICTP-SAIFR