Testing stationarity for stock market data

DOI10.1016/0165-1765(95)00744-XzbMath0875.90175OpenAlexW2020318454MaRDI QIDQ1351737

Jacek Leśkow, Dominique Dehay

Publication date: 27 February 1997

Published in: Economics Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0165-1765(95)00744-x

zbMATH Keywords

GARCH modelVolatilityTest of stationarity

Mathematics Subject Classification ID

Economic time series analysis (91B84) Statistical methods; economic indices and measures (91B82)

Related Items (4)

Asymptotic distributions and subsampling in spectral analysis for almost periodically correlated time series ⋮ Subsampling in testing autocovariance for periodically correlated time series ⋮ Consistency and application of moving block bootstrap for non-stationary time series with periodic and almost periodic structure ⋮ The impact of stationarity assessment on studies of volatility and value-at-risk.

Cites Work

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• ARCH modeling in finance. A review of the theory and empirical evidence
• Filtering and forecasting with misspecified ARCH models I. Getting the right variance with the wrong model
• Estimation of the Fourier coefficient functions and their spectral densities for \(\phi\)-mixing almost periodically correlated processes
• Asymptotic normality of the spectral density estimators for almost periodically correlated stochastic processes
• Testing for covariance stationarity in stock market data
• Functional limit theory for the spectral covariance estimator

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