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The empirical distribution function and partial sum process of residuals from a stationary arch with drift process
Authors:Janusz Kawczak  Reg Kulperger  Hao Yu
Institution:(1) Department of Mathematics and Statistics, University of North Carolina, 28223 Charlotte, NC, USA;(2) Department of Statistical and Actuarial Science, University of Western Ontario, N6A 5B7 London, Canada
Abstract:The weak convergence of the empirical process and partial sum process of the residuals from a stationary ARCH-M model is studied. It is obtained for and 
$$\sqrt n $$
consistent estimate of the ARCH-M parameters. We find that the limiting Gaussian processes are no longer distribution free and hence residuals cannot be treated as i.i.d. In fact the limiting Gaussian process for the empirical process is a standard Brownian bridge plus an additional term, while the one for partial sum process is a standard Brownian motion plus an additional term. In the special case of a standard ARCH process, that is an ARCH process with no drift, the additional term disappears. We also study a sub-sampling technique which yields the limiting Gaussian processes for the empirical process and partial sum process as a standard Brownian bridge and a standard Brownian motion respectively.
Keywords: and phrases" target="_blank"> and phrases  Weak convergence  residuals  ARCH  drift  empirical distribution
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