Modelling squared returns using a SETAR model with long-memory dynamics

DOI10.1016/j.econlet.2004.07.014zbMath1254.91654OpenAlexW1996869312MaRDI QIDQ1927744

Anne Peguin-Feissolle, Dominique Guégan, Gilles Dufrénot

Publication date: 2 January 2013

Published in: Economics Letters (Search for Journal in Brave)

Full work available at URL: https://halshs.archives-ouvertes.fr/halshs-00179285/file/Guegan-dufrenot-peguin_econletter2005.pdf

zbMATH Keywords

long-memoryFARIMA modelsstock indicesSETAR

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Economic time series analysis (91B84) Statistical methods; economic indices and measures (91B82)

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Modelling squared returns using a SETAR model with long-memory dynamics ⋮ A generalized ARFIMA model with smooth transition fractional integration parameter ⋮ Time-varying persistence of inflation: evidence from a wavelet-based approach ⋮ A simple fractionally integrated model with a time-varying long memory parameter \(d_t\) ⋮ How can we Define the Concept of Long Memory? An Econometric Survey ⋮ Forecasting realised volatility using ARFIMA and HAR models

Cites Work

• Long memory relationships and the aggregation of dynamic models
• A nonlinear long memory model, with an application to US unemployment.
• Modelling squared returns using a SETAR model with long-memory dynamics
• Modeling and Forecasting Realized Volatility

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