It is now widespread the use of the Value-at-Risk (VaR) as a canonical measure of risk. Most
accurate VaR measures make use of some volatility model such as GARCH-type models. …

This paper is concerned with the statistical modeling of the dependence structure of multivariate
financial data using the concept of copulas. We select some special copulas and identify …

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 …

The modeling of the extremal dependence structure can be made through parametric models
classified in two families: Logistic and Mixed, which contain the symmetric and asymmetric …

Data with asymmetric heavy tails can arise from mixture of data from multiple populations or
processes. We propose a computer intensive procedure to fit by quasi-maximum likelihood a …

It is well known that Gaussian maximum likelihood estimates of time series models are not
robust. In this paper we prove this is also the case for the Generalized Autoregressive …

We assess the extent of integration between stock markets during stressful periods using
the concept of copulas. Our methodology consists of fitting copulas to simultaneous …

Financial managers are mainly concerned about long lasting accumulated large losses
which may lead to massive money withdrawals. To assess this risk feeling we compute 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 …

Long memory in volatility is a stylized fact found in most financial return series. This paper
empirically investigates the extent to which interdependence in emerging markets may be …