Doubly fractional models for dynamic heteroskedastic cycles

Miguel Manuel Artiach Escauriaza and Josu Arteche

No 1134-8984, BILTOKI from Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística)

Abstract: Strong persistence is a common phenomenon that has been documented not only in the levels but also in the volatility of many time series. The class of doubly fractional models is extended to include the possibility of long memory in cyclical (non-zero) frequencies in both the levels and the volatility and a new model, the GARMA-GARMASV (Gegenbauer AutoRegressive Mean Average - Id. Stochastic Volatility) is introduced. A sequential estimation strategy, based on the Whittle approximation to maximum likelihood is proposed and its finite sample performance is evaluated with a Monte Carlo analysis. Finally, a trifactorial in the mean and bifactorial in the volatility version of the model is proved to successfully fit the well-known sunspot index.

Keywords: stochastic volatility; cycles; long memory; QML estimation; sunspot index (search for similar items in EconPapers)
Date: 2011-02
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Journal Article: Doubly fractional models for dynamic heteroscedastic cycles (2012)
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Dpto. de Econometría y Estadística, Facultad de CC. Económicas y Empresariales, Universidad del País Vasco, Avda. Lehendakari Aguirre 83, 48015 Bilbao, Spain

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