Abstract #301040

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JSM 2003 Abstract #301040
Activity Number: 98
Type: Contributed
Date/Time: Monday, August 4, 2003 : 9:00 AM to 10:50 AM
Sponsor: General Methodology
Abstract - #301040
Title: Effect of ARMA Model Misspecification on Prediction
Author(s): Shuguang Chen*+ and Igor Zurbenko
Companies: University at Albany and University of Albany
Address: 1499 3rd St., Rensselaer, NY, 12144,
Keywords: ARMA model ; prediction ; converge in distribution ; distance measures
Abstract:

Stability of ARMA model prediction is investigated over small errors in the model identification. At the stage of model identification of time series modeling, several tentative models are indicated. Usually model selection is based on model fit such as AIC, BIC. We examined the prediction stability of ARMA models using distance measures. We use distance measure of two ARMA models in Hilbert space to investigate the effect of two similar models on prediction. We show that if two models are close enough (converge in L2 space) then predictions from these two models converge in distribution. The rate of convergence and distance between two models are studied. Simulation is used to validate our results.

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