Copula Based VaR Estimation for Portfolio Using Hierarchical Clustering
This paper focuses on constructing models that predict a Value at Risk (VaR) estimation for financial portfolios using hierarchical clustering and copulas. Traditional VaR models often assume linear dependencies and normal distributions, which can be poor assumptions for financial data - especially during extreme market events. This paper introduces a non-linear modeling approach using copulas to
