Time series modelling of sunspot numbers using long range cyclical dependence
This paper deals with the analysis of the monthly structure of sunspot numbers using a new technique based on cyclical long range dependence. The results show that sunspot numbers have a periodicity of 130 months, but more importantly, that the series is highly persistent, with an order of cyclical fractional integration slightly above 0.30. That means that the series displays long memory, with a large degree of dependence between the observations that tends to disappear very slowly in time
|Date of creation:||01 Nov 2009|
|Contact details of provider:|| Web page: http://www.unav.edu/web/facultad-de-ciencias-economicas-y-empresariales|
References listed on IDEAS
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- Ferrara, Laurent & Guegan, Dominique, 2001.
"Forecasting with k-Factor Gegenbauer Processes: Theory and Applications,"
Journal of Forecasting,
John Wiley & Sons, Ltd., vol. 20(8), pages 581-601, December.
- Laurent Ferrara & Dominique Guegan, 2001. "Forecasting with k-factor Gegenbauer Processes: Theory and Applications," Post-Print halshs-00193667, HAL.
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- L.A. Gil-Alanaa, 2007. "Testing The Existence of Multiple Cycles in Financial and Economic Time Series," Annals of Economics and Finance, Society for AEF, vol. 8(1), pages 1-20, May.
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- Dalla, Violetta & Hidalgo, Javier, 2005. "A parametric bootstrap test for cycles," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 219-261. Full references (including those not matched with items on IDEAS)
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