FIEGARCH, modulus asymmetric FILog-GARCH and trend-stationary dual long memory time series
Yuanhua Feng (),
Thomas Gries () and
Sebastian Letmathe ()
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Yuanhua Feng: Paderborn University
Thomas Gries: Paderborn University
Sebastian Letmathe: Paderborn University
No 156, Working Papers CIE from Paderborn University, CIE Center for International Economics
A novel long memory volatility model MAFILog-GARCH (modulus asymmetric FILog-GARCH) is introduced, which is closely related to the FIEGARCH, but has some advantages. A general dual long memory FARIMA with those models as error processes is defined. Moreover, a trend-stationary dual long memory model is pro- posed. The FIEGARCH and MAFILog-GARCH are first applied to returns of eight top US firms. It is found that their practical performances are comparable. Both are superior to the FIGARCH and FILog-GARCH. Further application provides evidence of trend-stationary dual long memory time series in different fields.
Keywords: Modulus asymmetric FILog-GARCH; FIEGARCH; dual long memory; trend-stationary dual long memory; implementation in R (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:pdn:ciepap:156
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