Time-varying Multi-regime Models Fitting by Genetic Algorithms

Francesco Battaglia and Mattheos Protopapas ()

No 9, Working Papers from COMISEF

Abstract: Many time series exhibit both nonlinearity and nonstationarity. Though both features have often been taken into account separately, few attempts have been proposed to model them simultaneously. We consider threshold models, and present a general model allowing for different regimes both in time and in levels, where regime transitions may happen according to self-exciting, or smoothly varying, or piecewise linear threshold modeling. Since fitting such a model involves the choice of a large number of structural parameters, we propose a procedure based on genetic algorithms, evaluating models by means of a generalized identification criterion. The performance of the proposed procedure is illustrated with a simulation study and applications to some real data.

Keywords: Nonlinear time series; Nonstationary time series; Threshold model (search for similar items in EconPapers)
Pages: 37 pages
Date: 2009-02-20
New Economics Papers: this item is included in nep-cmp, nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Journal Article: Time‐varying multi‐regime models fitting by genetic algorithms (2011)
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