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Consistency of a nonparametric least squares estimator in integer-valued GARCH models

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  • Maximilian Wechsung
  • Michael H. Neumann

Abstract

We consider a nonparametric version of the integer-valued GARCH(1,1) model for time series of counts. The link function in the recursion for the variances is not specified by finite-dimensional parameters. Instead we impose nonparametric smoothness conditions. We propose a least squares estimator for this function and show that it is consistent with a rate that we conjecture to be nearly optimal.

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  • Maximilian Wechsung & Michael H. Neumann, 2022. "Consistency of a nonparametric least squares estimator in integer-valued GARCH models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 34(2), pages 491-519, April.
    • Handle: RePEc:taf:gnstxx:v:34:y:2022:i:2:p:491-519
    DOI: 10.1080/10485252.2022.2043310
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