Modelling financial time series with SEMIFAR-GARCH model

Yuanhua Feng, Jan Beran and Keming Yu

MPRA Paper from University Library of Munich, Germany

Abstract: A class of semiparametric fractional autoregressive GARCH models (SEMIFAR-GARCH), 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)
JEL-codes: C14 C22 G00 (search for similar items in EconPapers)
Date: 2006
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Related works:
Working Paper: Modelling financial time series with SEMIFAR-GARCH model (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:1593

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