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Econometric estimation in long–range dependent volatility models: theory and practice

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Casas, Isabel; Gao, Jiti

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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.
Classification Economics
Free Keywords continuous–time model; diffusion process; long–range dependence; stochastic volatility
Document language English
Publication Year 2008
Page/Pages p. 72-83
Journal Journal of Econometrics, 147 (2008) 1
Status Postprint; peer reviewed
Licence PEER Licence Agreement (applicable only to documents from PEER project)