GitLab

Trading strategy for the S&P 500 index based on ARIMA models.

2D DEM simulation showing brazil nut effect

This includes an implementation of Conditional Variational Autoencoders (CVAE).

Machine learning model that uses signatures to recognise handwritten signatures.

ESGI116 Technip Project on Umbilical Optimised Design

Use of genetic algorithms for a simple trading strategy, in C++.

Signature-based machine learning model that predicts, given daily data of a stock (more specifically, the evolution of its price and volume) which country the stock trades in.

This repository contains the updated code that is being used in the Machine Learning reading group organised by Terry Lyons.

MonteCarlo and Arima for stock selection

project with maria

Pair trading in C++