Multi-regime models for nonlinear nonstationary time series
AbstractNonlinear nonstationary models for time series are considered, where the series is generated from an autoregressive equation whose coe±cients change both according to time and the delayed values of the series itself, switching between several regimes. The transition from one regime to the next one may be discontinuous (self-exciting threshold model), smooth (smooth transition model) or continuous linear (piecewise linear threshold model). A genetic algorithm for identifying and estimating such models is proposed, and its behavior is evaluated through a simulation study and application to temperature data and a financial index.
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Bibliographic InfoPaper provided by COMISEF in its series Working Papers with number 026.
Length: 21 pages
Date of creation: 28 Jan 2010
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-04-17 (All new papers)
- NEP-ECM-2010-04-17 (Econometrics)
- NEP-ETS-2010-04-17 (Econometric Time Series)
- NEP-ORE-2010-04-17 (Operations Research)
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