EN
We discuss generalisation of the conditional distribution in GARCH model and present empirical analysis indicating its empirical importance. The model is a generalised version of those presented in Pipień (2007, 2010). The flexibility of the construct involves the existence of a set of coordinates along which the fat tails and asymmetry can be modelled. In the conditional distribution both linear and nonlinear dependence between individual returns can be modelled, while the latter being described by the copula function. In the empirical part of the paper the dynamics and dependence of daily returns of WIG20 SPOT and FUTURES are discussed.