Semiparametric estimation in perturbed long memory series

DOI10.1016/j.csda.2006.07.023zbMath1157.62486OpenAlexW2009513343MaRDI QIDQ1010559

Josu Arteche

Publication date: 6 April 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2006.07.023

zbMATH Keywords

stochastic volatilitysemiparametric estimationperturbed long memory

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Nonparametric estimation (62G05) Inference from stochastic processes and spectral analysis (62M15)

Related Items (14)

When long memory meets the Kalman filter: a comparative study ⋮ SIGNAL EXTRACTION IN LONG MEMORY STOCHASTIC VOLATILITY ⋮ A bootstrap approximation for the distribution of the local Whittle estimator ⋮ Semiparametric Inference in Correlated Long Memory Signal Plus Noise Models ⋮ Wavelet semi-parametric inference for long memory in volatility in the presence of a trend ⋮ Semiparametric nonlinear log-periodogram regression estimation for perturbed stationary anisotropic long memory random fields ⋮ Whittle-type estimation under long memory and nonstationarity ⋮ Using the bootstrap for finite sample confidence intervals of the log periodogram regression ⋮ Modified local Whittle estimator for long memory processes in the presence of low frequency (and other) contaminations ⋮ Local polynomial Whittle estimation of perturbed fractional processes ⋮ Bootstrap-based bandwidth choice for log-periodogram regression ⋮ Generalised long-memory GARCH models for intra-daily volatility ⋮ Modelling long-memory volatilities with leverage effect: A-LMSV versus FIEGARCH ⋮ The role of long memory in hedging effectiveness

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