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In testing that a given distribution belongs to a parameterized family , one is often led to compare a nonparametric estimate
of some functional of with an element
corresponding to an estimate
of . In many cases, the asymptotic distribution of goodness-of-fit statistics derived from the process
(
−
) depends on the unknown distribution . It is shown here that if the sequences
and
...
In this paper we present a forecasting method for time series using copula-based models for multivariate time series. We study how the performance of the predictions evolves when changing the strength of the different possible dependencies, as well as the structure of the dependence. We also look at the impact of the marginal distributions. The impact of estimation errors on the performance of the predictions is also considered. In all the experiments, we compare predictions from our multivariate...
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