Estimation of the long-memory stochastic volatility model parameters that is robust to level shifts and deterministic trends

DOI10.1111/jtsa.12012zbMath1273.62217OpenAlexW1645341287MaRDI QIDQ2852592

Adam McCloskey

Publication date: 9 October 2013

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://economics.brown.edu/sites/g/files/dprerj726/files/papers/2012-17_paper.pdf

zbMATH Keywords

stochastic volatilityrobust estimationstructural changelong-memorydeterministic trendslevel shiftsfrequency domain estimationspurious persistence

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Point estimation (62F10)

Related Items (7)

Autoregressive spectral estimates under ignored changes in the mean ⋮ Estimation and forecasting of long memory stochastic volatility models ⋮ Wavelet semi-parametric inference for long memory in volatility in the presence of a trend ⋮ Trimmed Whittle estimation of the SVAR vs. filtering low-frequency fluctuations: applications to technology shocks ⋮ Asymptotic theory for time series with changing mean and variance ⋮ Medium band least squares estimation of fractional cointegration in the presence of low-frequency contamination ⋮ Modified local Whittle estimator for long memory processes in the presence of low frequency (and other) contaminations

Cites Work

• Forecasting realized volatility using a long-memory stochastic volatility model: estimation, prediction and seasonal adjustment
• Efficient parameter estimation for self-similar processes
• Large-sample properties of parameter estimates for strongly dependent stationary Gaussian time series
• Non-stationary log-periodogram regression
• A limit theory for long-range dependence and statistical inference on related models
• Large-sample inference for nonparametric regression with dependent errors
• The detection and estimation of long memory in stochastic volatility
• Nonlinear log-periodogram regression for perturbed fractional processes
• Log-periodogram regression of time series with long range dependence
• Local Whittle estimation of the memory parameter in presence of deterministic components
• A Test Against Spurious Long Memory
• Long-Memory and Level Shifts in the Volatility of Stock Market Return Indices
• THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS
• Properties of the Sieve Bootstrap for Fractionally Integrated and Non-Invertible Processes
• Discrimination between monotonic trends and long-range dependence
• The mean squared error of Geweke and Porter-Hudak's estimator of the memory parameter of a long-memory time series
• ASYMPTOTICS FOR THE LOW-FREQUENCY ORDINATES OF THE PERIODOGRAM OF A LONG-MEMORY TIME SERIES
• ESTIMATION OF THE MEMORY PARAMETER FOR NONSTATIONARY OR NONINVERTIBLE FRACTIONALLY INTEGRATED PROCESSES
• ON THE LOG PERIODOGRAM REGRESSION ESTIMATOR OF THE MEMORY PARAMETER IN LONG MEMORY STOCHASTIC VOLATILITY MODELS
• MEMORY PARAMETER ESTIMATION IN THE PRESENCE OF LEVEL SHIFTS AND DETERMINISTIC TRENDS
• Estimating Long Memory in Volatility
• Adaptive Local Polynomial Whittle Estimation of Long-range Dependence
• The asymptotic theory of linear time-series models
• Finite sample properties of a QML estimator of stochastic volatility models with long memory.
• Long memory and regime switching

This page was built for publication: Estimation of the long-memory stochastic volatility model parameters that is robust to level shifts and deterministic trends