computed after risk neutralization of the multivariate process which is estimated under the physical probability measure. The …

We introduce a new, factor based bootstrap approach which is robust under heteroskedastic error terms for inference in … functional coefficient models. Modeling the functional coefficient parametrically, the bootstrap approximation of an F statistic …, factor based bootstrap inference outperforms the wild bootstrap and pairs bootstrap approach according to its size features …

To infer on functional dependence of regression parameters, a new, factor based bootstrap approach is introduced that … bootstrap approximation of an F-statistic is shown to hold asymptotically. In simulation studies with both parametric and … nonparametric functional coefficients, factor based bootstrap inference outperforms the wild bootstrap and pairs bootstrap approach …

conditional heteroskedasticity. We show that the wild bootstrap provides convenient critical values for the considered OLS …-based statistics under both homoskedastic and conditionally heteroskedastic model errors. The wild bootstrap is easy to implement and … approximations. We prove further that the wild bootstrap retains its validity for inference within a system of pooled equations …

confirmed in a simulation study. We summarize serial correlation robust test procedures and propose a bootstrap approach. By …

confirmed in a simulation study. We summarize serial correlation robust test procedures and propose a bootstrap approach. By …. -- Directional forecasts ; directional accuracy ; forecast evaluation ; testing independence ; contingency tables ; bootstrap …