Arbeitspapier

Bahadur Representation for the Nonparametric M-Estimator Under Alpha-mixing Dependence

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=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.

Sprache
Englisch

Erschienen in
Series: Tinbergen Institute Discussion Paper ; No. 05-067/4

Klassifikation
Wirtschaft
Semiparametric and Nonparametric Methods: General
Thema
Asymptotic representation
Kernel function
Robust estimator
Strongly-mixing
Schätztheorie
Nichtparametrisches Verfahren
Theorie

Ereignis
Geistige Schöpfung
(wer)
Cheng, Yebin
de Gooijer, Jan G.
Ereignis
Veröffentlichung
(wer)
Tinbergen Institute
(wo)
Amsterdam and Rotterdam
(wann)
2005

Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

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Objekttyp

  • Arbeitspapier

Beteiligte

  • Cheng, Yebin
  • de Gooijer, Jan G.
  • Tinbergen Institute

Entstanden

  • 2005

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