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

Journal article | Zeitschriftenartikel

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.

Object Details

• Extent: Seite(n): 72-83
• Language: Englisch
• Notes: Status: Postprint; begutachtet (peer reviewed)

References and Relationships

• Bibliographic citation: Journal of Econometrics, 147(1)

Classification and Topics

• Subject: Wirtschaft ; Wirtschaftswissenschaften

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Casas, Isabel ; Gao, Jiti
• Event: Veröffentlichung
• (where): Niederlande
• (when): 2008

Further information

• DOI: https://doi.org/10.1016/j.jeconom.2008.09.035
• URN: urn:nbn:de:0168-ssoar-201031
• Rights: GESIS - Leibniz-Institut für Sozialwissenschaften. Bibliothek Köln
• Last update: 21.06.2024, 4:27 PM CEST