Modelling financial time series with SEMIFAR-GARCH model

Yuanhua Feng (), Jan Beran and Keming Yu

No 07-14, CoFE Discussion Paper from Center of Finance and Econometrics, University of Konstanz

Abstract: A class of semiparametric fractional autoregressive GARCH models (SEMIFARGARCH), which includes deterministic trends, difference stationarity and stationarity with short- and 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 term. So that the model can be applied in practice. We then illustrate the model and estimation methods with a few of different finance data sets.

Keywords: Financial time series; GARCH model; SEMIFAR model; parameter estimation; kernel estimation; asymptotic property. (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-fmk
Date: 2007-12-01
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Related works:
Working Paper: Modelling financial time series with SEMIFAR-GARCH model (2006)
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