A SETAR model with long-memory dynamics
AbstractThis paper presents a 2-regime SETAR model where the process under examination is governed by a long-memory process in the first regime and a short-memory process in the second regime. Persistence properties are studied and methods for locating the threshold parameter are proposed. Such a process presents a useful application to financial data and is applied to stock indices and individual assets.
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Date of creation: 04 Sep 2003
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Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing
This paper has been announced in the following NEP Reports:
- NEP-ALL-2003-09-08 (All new papers)
- NEP-ECM-2003-09-08 (Econometrics)
- NEP-ETS-2003-09-08 (Econometric Time Series)
- NEP-FIN-2003-09-08 (Finance)
- NEP-MAC-2003-09-08 (Macroeconomics)
- NEP-RMG-2003-09-08 (Risk Management)
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- Ferrara, Laurent & Guégan, Dominique, 2005.
"Detection of the industrial business cycle using SETAR models,"
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- Laurent Ferrara & Dominique Guégan, 2005. "Detection of the Industrial Business Cycle using SETAR Models," Journal of Business Cycle Measurement and Analysis, OECD Publishing,CIRET, vol. 2005(3), pages 353-371.
- Dominique Guegan & Laurent Ferrara, 2005. "Detection of the Industrial Business Cycle using SETAR models," Post-Print halshs-00201309, HAL.
- Kuswanto, Heri & Sibbertsen, Philipp, 2008. "A Study on "Spurious Long Memory in Nonlinear Time Series Models"," Diskussionspapiere der Wirtschaftswissenschaftlichen FakultÃ¤t der Leibniz UniversitÃ¤t Hannover dp-410, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
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