Modelling financial time series with SEMIFAR GARCH model

  • Y.Feng
  • J.Beran
  • K.Yu

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Modelling financial time series with SEMIFAR-GARCH model

A class of semiparametric fractional autoregressive GARCH models (SEMIFARGARCH), which includes deterministic trends, difference stationarity and stationarity with shortand long-range dependence, and heteroskedastic model errors, is very powerful for modelling financial time series. This paper discusses the model fitting, including an efficient algorithm and parameter estimation of GARCH error ...

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Nowadays many researchers use GARCH models to generate volatility forecasts. However, it is well known that volatility persistence, as indicated by the sum of the two parameters G1 and A1[1], in GARCH models is usually too high. Since volatility forecasts in GARCH models are based on these two parameters, this may lead to poor volatility forecasts. It has long been argued that this high persist...

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Article info

Journal name: IMA Journal of Management Mathematics

Year: 2007

ISSN: 1471-678X,1471-6798

DOI: 10.1093/imaman/dpm024