  The t copula is often used in risk management as it allows for modelling tail
dependence between risks and it is simple to simulate and calibrate. However,
the use of a standard t copula is often criticized due to its restriction of
having a single parameter for the degrees of freedom (dof) that may limit its
capability to model the tail dependence structure in a multivariate case. To
overcome this problem, grouped t copula was proposed recently, where risks are
grouped a priori in such a way that each group has a standard t copula with its
specific dof parameter. In this paper we propose the use of a grouped t copula,
where each group consists of one risk factor only, so that a priori grouping is
not required. The copula characteristics in the bivariate case are studied. We
explain simulation and calibration procedures, including a simulation study on
finite sample properties of the maximum likelihood estimators and Kendall's tau
approximation. This new copula can be significantly different from the standard
t copula in terms of risk measures such as tail dependence, value at risk and
expected shortfall.
  Keywords: grouped t copula, tail dependence, risk management.
