Semiparametric Inference in Correlated Long Memory Signal Plus Noise Models

DOI10.1080/07474938.2011.607996zbMath1491.62084OpenAlexW3021168763MaRDI QIDQ5080154

Josu Arteche

Publication date: 31 May 2022

Published in: Econometric Reviews (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10810/5570

zbMATH Keywords

long memorysemiparametric inferencelog periodogram regressionsignal plus noise

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Inference from stochastic processes and spectral analysis (62M15)

Related Items (2)

Estimation of Long Memory in Integrated Variance ⋮ Wavelet semi-parametric inference for long memory in volatility in the presence of a trend

Cites Work

• Gaussian semiparametric estimation in long memory in stochastic volatility and signal plus noise models
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• Nonlinear log-periodogram regression for perturbed fractional processes
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• Adaptive semiparametric estimation of the memory parameter.
• Bootstrap-based bandwidth choice for log-periodogram regression
• Corrigendum to "Estimating Long Memory in Volatility"
• Refined Inference on Long Memory in Realized Volatility
• The mean squared error of Geweke and Porter-Hudak's estimator of the memory parameter of a long-memory time series
• ON THE LOG PERIODOGRAM REGRESSION ESTIMATOR OF THE MEMORY PARAMETER IN LONG MEMORY STOCHASTIC VOLATILITY MODELS
• TESTING FOR LONG MEMORY IN VOLATILITY
• NON-GAUSSIAN LOG-PERIODOGRAM REGRESSION
• Estimating Long Memory in Volatility
• Modeling and Forecasting Realized Volatility

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