Doubly fractional models for dynamic heteroscedastic cycles

Publication year: 2011 Source: Computational Statistics & Data Analysis, Available online 22 October 2011 Miguel Artiach, Josu Arteche Strong cyclical persistence is a common phenomenon that has been documented not only in the levels but also in the volatility of many time series, specially in astronomical or business cycle data. The class of doubly fractional models is extended to include the possibility of long memory in cyclical (non-zero) frequencies in both levels and volatility and a new model, the GARMA-GARMASV (Gegenbauer AutoRegressive Mean Average – Id

Publication year: 2011 Source: Computational Statistics & Data Analysis, Available online 22 October 2011 Miguel Artiach, Josu Arteche Strong cyclical persistence is a common phenomenon that has been documented not only in the levels but also in the volatility of many time series, specially in astronomical or business cycle data. The class of doubly fractional models is extended to include the possibility of long memory in cyclical (non-zero) frequencies in both levels and volatility and a new model, the GARMA-GARMASV (Gegenbauer AutoRegressive Mean Average – Id

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Doubly fractional models for dynamic heteroscedastic cycles

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