TOOLS FOR NON-LINEAR TIME SERIES FORECASTING IN ECONOMICS – AN EMPIRICAL COMPARISON OF REGIME SWITCHING VECTOR AUTOREGRESSIVE MODELS AND RECURRENT NEURAL NETWORKS

Jane M. Binner, Thomas Elger, Birger Nilsson and Jonathan A. Tepper

A chapter in Applications of Artificial Intelligence in Finance and Economics, 2004, pp 71-91 from Emerald Group Publishing Limited

Abstract: The purpose of this study is to contrast the forecasting performance of two non-linear models, a regime-switching vector autoregressive model (RS-VAR) and a recurrent neural network (RNN), to that of a linear benchmark VAR model. Our specific forecasting experiment is U.K. inflation and we utilize monthly data from 1969 to 2003. The RS-VAR and the RNN perform approximately on par over both monthly and annual forecast horizons. Both non-linear models perform significantly better than the VAR model.

Date: 2004
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Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-9053(04)19003-8

DOI: 10.1016/S0731-9053(04)19003-8

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