Portfolio level (un)conditional risk measure estimation for backtesting using Vine Copula and ARMA-GARCH models.
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Updated
Jan 22, 2024 - R
Portfolio level (un)conditional risk measure estimation for backtesting using Vine Copula and ARMA-GARCH models.
Automatic optimal sequential investment decisions. Forecasts made using advanced stochastic processes with Monte Carlo simulation. Dependency is handled with vine copulas.
MATVines: A Vine Copula Package for MATLAB. To cite this software publication: https://www.sciencedirect.com/science/article/pii/S2352711021000455
D-Vine GAM Copula based Quantile Regression
Code for the case studies and theoretical visualizations for the master thesis 'Estimation and Backtesting of the Expected Shortfall and Value at Risk using Vine Copulas'
Gradient-Boosted Estimation of Generalized Linear Models for Conditional Vine Copulas
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