Financial returns often present a complex relation with previous observations, along with a slight skewness and high kurtosis. As a consequence, we must pursue the use of flexible models that are able to seize these special features: a financial process that can expose the intertemporal relation...

Financial returns often present moderate skewness and high kurtosis. As a consequence, it is natural to look for a model that is exible enough to capture these characteristics. The proposal is to undertake inference for a generalized autoregressive conditional heteroskedastic (GARCH) model,...

The adequacy of GARCH models is often analyzed by comparing plug-in and sample kurtosis and autocorrelations of squares. We analyse the finite sample suitability of this comparison and show that it is not appropiate in general.