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@article{ Casas2008, title = {Econometric estimation in long–range dependent volatility models: theory and practice}, author = {Casas, Isabel and Gao, Jiti}, journal = {Journal of Econometrics}, number = {1}, pages = {72-83}, volume = {147}, year = {2008}, doi = {https://doi.org/10.1016/j.jeconom.2008.09.035}, urn = {https://nbn-resolving.org/urn:nbn:de:0168-ssoar-201031}, abstract = {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.}, }