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%T Econometric estimation in long–range dependent volatility models: theory and practice %A Casas, Isabel %A Gao, Jiti %J Journal of Econometrics %N 1 %P 72-83 %V 147 %D 2008 %K continuous–time model; diffusion process; long–range dependence; stochastic volatility %= 2010-11-08T09:07:00Z %~ http://www.peerproject.eu/ %> https://nbn-resolving.org/urn:nbn:de:0168-ssoar-201031 %X It is commonly accepted that some financial data may exhibit long-range dependence, while other financial data exhibit intermediate-range dependence or short-range dependence. These behaviours may be fitted to a continuous-time fractional stochastic model. The estimation procedure proposed in this paper is based on a continuous-time version of the Gauss–Whittle objective function to find the parameter estimates that minimize the discrepancy between the spectral density and the data periodogram. As a special case, the proposed estimation procedure is applied to a class of fractional stochastic volatility models to estimate the drift, standard deviation and memory parameters of the volatility process under consideration. As an application, the volatility of the Dow Jones, S&P 500, CAC 40, DAX 30, FTSE 100 and NIKKEI 225 is estimated. %C NLD %G en %9 journal article %W GESIS - http://www.gesis.org %~ SSOAR - http://www.ssoar.info