Gaussian inference on certain long-range dependent volatility models

DOI10.1016/S0304-4076(03)00096-4zbMath1027.62074OpenAlexW1995799665MaRDI QIDQ1398961

Banca d'Italia, Paolo Zaffaroni

Publication date: 7 August 2003

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0304-4076(03)00096-4

zbMATH Keywords

Long memoryWhittle estimationNonlinear moving average modelVolatility model

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Applications of statistics to actuarial sciences and financial mathematics (62P05)

Related Items (8)

Modelling structural breaks, long memory and stock market volatility: an overview ⋮ Whittle estimation of EGARCH and other exponential volatility models ⋮ Long-memory in high-frequency exchange rate volatility under temporal aggregation ⋮ Uniform limit theorems for the integrated periodogram of weakly dependent time series and their applications to Whittle's estimate ⋮ NONSTATIONARITY-EXTENDED WHITTLE ESTIMATION ⋮ \(L_1\)-estimation for the location parameters in stochastic volatility models ⋮ Pseudo-maximum likelihood estimation of \(\text{ARCH}(\infty)\) models ⋮ Estimating the memory parameter for potentially non-linear and non-Gaussian time series with wavelets

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