Multivariate data modelling with Copulas in Python
Python package for canonical vine copula trees with mixed continuous and discrete marginals
Matlab toolbox for canonical vine copula trees with mixed continuous and discrete marginals
Inference for Gaussian copula factor models and its application to causal discovery.
Copula fitting in Python.
Copula-based Hidden Markov Model (HMM) to decode tactics in a football match. Final project for the Probabilistic Machine Learning course of the MSc degree in Data Science and Artificial Intelligence (DSAI), University of Trieste
The repo contains the main topics carried out in my master's thesis on operational risk. In particular, it is described how to implement the so called Loss Distribution Approach (LDA), which is considered the state-of-the-art method to compute capital charge among large banks.
Robust Estimation of Copulas by Maximum Mean Discrepancy
Examples of scheduled jobs estimating copulas at www.microprediction.org
Python library for modelling complex multivariate dependencies using stochastic copulas
Portfolio credit risk modeling
Causal discovery from mixed data with missing values.
In this project, we predict the probability of occurrence of risk in the Indian territory, based on the historical data of precipitation and temperature between the years 1951 - 2015
A rudimentary collection of risk methods in finance.
My bachelor's thesis about portfolio VaR forecasting with multivariate factor copula-GARCH models
Multivariate Environmental Statistics (BEE6300) R Code
Simulation of Partition-of-Unity copulas in R, e.g. for the purpose of modeling risk or for the creation of synthetic data based on restricted datasets
Copula-based modeling of financial asset dependencies during the 2008 Global Financial Crisis and COVID-19, capturing nonlinear and tail risk dynamics
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