Abstract #301522

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JSM 2002 Abstract #301522
Activity Number: 65
Type: Topic Contributed
Date/Time: Monday, August 12, 2002 : 8:30 AM to 10:20 AM
Sponsor: Business & Economics Statistics Section*
Abstract - #301522
Title: Nonlinear Time Series Model Identification and Estimation via Resampling
Author(s): Lori Thombs*+ and Katherine Ensor
Affiliation(s): University of South Carolina and Rice University
Address: Univ of South Carolina, Columbia, South Carolina, 29208, USA
Keywords: nonlinear time series ; bootstrap resampling ; autocorrelation
Abstract:

The research is in the general area of estimation for nonlinear time series models, with specific attention being given to the GARCH model. It is known that the squared GARCH process has a correlation structure which is the same as an ARMA process, but with innovations that are uncorrelated but not independent. This subtle difference can affect the usual variance estimates for sample autocorrelations, leading to incorrect model identification, estimation, and inference. It is the uncorrelated but not independent structure to the process that is the focus of our efforts. Combining the recent results in the fields of economic time series (Baillie and Chung, 2001) and bootstrapping time series (Romano and Thombs, 1996), we propose new methods of estimation for nonlinear time series models.

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