Download This PaperSelecting Nonlinear Time Series Models Using Information Criteria
26 Pages Posted: 20 Jun 2009
Date Written: 0000
Abstract
This article considers the problem of selecting among competing nonlinear time series models by using complexity-penalized likelihood criteria. An extensive simulation study is undertaken to assess the small-sample performance of several popular criteria in selecting among nonlinear autoregressive models belonging to some families that have been popular with practitioners.
Suggested Citation: Suggested Citation
Psaradakis, Zacharias and Sola, Martín and Spagnolo, Fabio and Spagnolo, Nicola, Selecting Nonlinear Time Series Models Using Information Criteria (0000). Journal of Time Series Analysis, Vol. 30, Issue 4, pp. 369-394, July 2009, Available at SSRN: https://ssrn.com/abstract=1423148 or http://dx.doi.org/10.1111/j.1467-9892.2009.00614.x
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