We demonstrate that, for any 1[less-than-or-equals, slant]p[infinity], the Lp-distance between the kernel density estimators of the residuals and errors in the first-order autoregressive models is so small that the asymptotic behaviour of the Lp-distance between the kernel density estimator of...

The unconditional variance of various GARCH-type models is a function h(theta) of the parameter vector theta which is estimated by theta. For most models used in practice, closed-form expressions of h(.) have been found. On the contrary, the unconditional variance can be estimated by the sample...

We demonstrate that, for any 1[less-than-or-equals, slant]p[infinity], the Lp-distance between the kernel density estimators of the residuals and errors in the first order autoregressive models is so small that the asymptotic behaviour of the Lp-distance between the kernel density estimator of...