Local polynomial Whittle estimation of perturbed fractional processes

DOI10.1016/j.jeconom.2011.09.026zbMath1441.62693OpenAlexW3023013505MaRDI QIDQ738169

Frank S. Nielsen, Morten Ørregaard Nielsen, Per Frederiksen

Publication date: 15 August 2016

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

Full work available at URL: http://ageconsearch.umn.edu/record/273704

zbMATH Keywords

bias reductionstochastic volatilitysemiparametric estimationlong memorylocal Whittleperturbed fractional process

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Fractional processes, including fractional Brownian motion (60G22) Inference from stochastic processes and spectral analysis (62M15)

Related Items (10)

A bootstrap approximation for the distribution of the local Whittle estimator ⋮ On the memory of products of long range dependent time series ⋮ ADAPTIVE LONG MEMORY TESTING UNDER HETEROSKEDASTICITY ⋮ Wavelet semi-parametric inference for long memory in volatility in the presence of a trend ⋮ A multivariate test against spurious long memory ⋮ Modified local Whittle estimator for long memory processes in the presence of low frequency (and other) contaminations ⋮ Consistent inference for predictive regressions in persistent economic systems ⋮ A Generalised Fractional Differencing Bootstrap for Long Memory Processes ⋮ MEMORY PARAMETER ESTIMATION IN THE PRESENCE OF LEVEL SHIFTS AND DETERMINISTIC TRENDS ⋮ Testing for parameter instability and structural change in persistent predictive regressions

Uses Software

• Ox
• longmemo

Cites Work

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• Gaussian semiparametric estimation in long memory in stochastic volatility and signal plus noise models
• Semiparametric estimation in perturbed long memory series
• Fractionally integrated generalized autoregressive conditional heteroskedasticity
• The detection and estimation of long memory in stochastic volatility
• Nonlinear log-periodogram regression for perturbed fractional processes
• Local Whittle estimation in nonstationary and unit root cases.
• Log-periodogram regression of time series with long range dependence
• Gaussian semiparametric estimation of long range dependence
• Long memory processes and fractional integration in econometrics
• Long memory in continuous-time stochastic volatility models
• THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS
• Tests for Hurst effect
• Gaussian Semiparametric Estimation of Non-stationary Time Series
• Multivariate Stochastic Variance Models
• 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
• The Distribution of Realized Exchange Rate Volatility
• LOG-PERIODOGRAM ESTIMATION OF LONG MEMORY VOLATILITY DEPENDENCIES WITH CONDITIONALLY HEAVY TAILED RETURNS
• Estimating Long Memory in Volatility
• Modeling and Forecasting Realized Volatility
• A Bias-Reduced Log-Periodogram Regression Estimator for the Long-Memory Parameter
• Adaptive Local Polynomial Whittle Estimation of Long-range Dependence
• A generalized bivariate mixture model for stock price volatility and trading volume

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