Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/86432
Authors: 
Cheng, Yebin
de Gooijer, Jan G.
Year of Publication: 
2005
Series/Report no.: 
Tinbergen Institute Discussion Paper 05-067/4
Abstract: 
Under the condition that the observations, which come from a high-dimensional population (X,Y), are strongly stationary and strongly-mixing, through using the local linear method, we investigate, in this paper, the strong Bahadur representation of the nonparametric M-estimator for the unknown function m(x)=arg minaIE(r(a,Y)=x), where the loss function r(a,y) is measurable. Furthermore, some related simulations are illustrated by using the cross validation method for both bivariate linear and bivariate nonlinear time series contaminated by heavy-tailed errors. The M-estimator is applied to a series of S&P 500 index futures andspot prices to compare its performance in practice with the usual squared-loss regression estimator.
Subjects: 
Asymptotic representation
Kernel function
Robust estimator
Strongly-mixing
JEL: 
C14
Document Type: 
Working Paper

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