Spectral Regression For Cointegrated Time Series With Long-Memory Innovations

DOI10.1111/1467-9892.00204zbMath0972.62089OpenAlexW3021833099MaRDI QIDQ2740045

Domenico Marinucci

Publication date: 16 September 2001

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

Full work available at URL: https://doi.org/10.1111/1467-9892.00204

zbMATH Keywords

asymptotic distributionparameter estimationquadratic formsautocovariance function

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Inference from stochastic processes and spectral analysis (62M15)

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The distance between rival nonstationary fractional processes ⋮ Modelling structural breaks, long memory and stock market volatility: an overview ⋮ Asymptotic inference results for multivariate long‐memory processes ⋮ Asymptotic normality of narrow-band least squares in the stationary fractional cointegration model and volatility forecasting ⋮ SPECTRAL FINANCIAL ECONOMETRICS ⋮ DEFINITIONS AND REPRESENTATIONS OF MULTIVARIATE LONG-RANGE DEPENDENT TIME SERIES ⋮ Using Difference-Based Methods for Inference in Regression with Fractionally Integrated Processes ⋮ Polynomial Cointegration Between Stationary Processes With Long Memory ⋮ Nonparametric frequency domain analysis of nonstationary multivariate time series ⋮ Fractional cointegration in the presence of linear trends ⋮ Likelihood based testing for no fractional cointegration ⋮ Fixed Bandwidth Inference for Fractional Cointegration ⋮ Narrow-band analysis of nonstationary processes ⋮ Small‐b and Fixed‐b Asymptotics for Weighted Covariance Estimation in Fractional Cointegration ⋮ A model of fractional cointegration, and tests for cointegration using the bootstrap.

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