A library to model multivariate data using copulas.

Multivariate data modelling with Copulas in Python

TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series, from ServiceNow Research

Python package for canonical vine copula trees with mixed continuous and discrete marginals

Code for paper "Copula-based conformal prediction for Multi-Target Regression"

Automatic optimal sequential investment decisions. Forecasts made using advanced stochastic processes with Monte Carlo simulation. Dependency is handled with vine copulas.

Matlab toolbox for canonical vine copula trees with mixed continuous and discrete marginals

MATVines: A Vine Copula Package for MATLAB. To cite this software publication: https://www.sciencedirect.com/science/article/pii/S2352711021000455

An R package for the stochastic simulation of processes with any marginal distribution and correlation structure

Robust Estimation of Copulas by Maximum Mean Discrepancy

This repository contains the code of our published work in IEEE JBHI. Our main objective was to demonstrate the feasibility of the use of synthetic data to effectively train Machine Learning algorithms, prooving that it benefits classification performance most of the times.

Examples of scheduled jobs estimating copulas at www.microprediction.org

Copula fitting in Python.

Semiparametric efficient rank-based estimation of copula parameters

A Python Package to Create Synthetic Tabular Data

Notebooks in financial mathematics. Ranging from risk management to portfolio management and stochastic processes for financial markets.

Mostly experiments of quantitative finance concepts that i wish to get a deeper knowledge of the underlying theory

Estimation and inference for conditional copulas models

Master's thesis - Assessment of cognitive load in extreme environment

Multivariate time series generator based on the Phase Annealing algorithm. Various objective functions that focus on multivariate copula properties while annealing. Various plotting routines to visualize results. Take a look at the scripts in the "test" directory for how to use.