This paper concerns itself with applications of pair-copulas in finance, and bridges the gap between theory and application. We provide a broad view of the problem of modeling multivariate financial log-returns using pair-copulas, gathering together for this purpose theoretical and computational...

Purpose – Proposes a new covariance matrix robust estimator able to capture the correct orientation of the data and the large unconditional variance caused by occasional high volatility periods. Design/methodology/approach – Derives easy-to-compute estimates for the center and covariance...

Purpose – This paper aims to statistically model the serial dependence in the first and second moments of a univariate time series using copulas, bridging the gap between theory and applications, which are the focus of risk managers. Design/methodology/approach – The appealing feature of the...

Purpose – Proposes a new covariance matrix robust estimator able to capture the correct orientation of the data and the large unconditional variance caused by occasional high volatility periods. Design/methodology/approach – Derives easy‐to‐compute estimates for the center and covariance...

Purpose – This paper aims to statistically model the serial dependence in the first and second moments of a univariate time series using copulas, bridging the gap between theory and applications, which are the focus of risk managers. Design/methodology/approach – The appealing feature of the...