ARMA-GARCH/APARCH Models with Stable, GEV and GAt Innovations

Simulation, estimation and forecasting of autoregressive moving average (ARMA) models with generalized autoregressive conditional heteroskedasticity (GARCH) or asymmetric power ARCH (APARCH, with ARCH the autoregressive conditional heteroskedasticity model) errors, with stable (S0 parametrization), generalized extreme value (GEV) and generalized asymmetric t (GAt) innovations. The innovation distribution is a pluggable object, so user defined densities get the same fitting, simulation, stationarity and forecasting machinery.