Nonparametric testing for long-horizon predictability with persistent covariates

DOI10.1080/10485252.2013.870173zbMath1359.62146OpenAlexW1989383462MaRDI QIDQ5419470

Jin Lee

Publication date: 6 June 2014

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485252.2013.870173

zbMATH Keywords

sieve bootstrapnonparametric estimatorlong-horizon predictability

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Nonparametric regression and quantile regression (62G08) Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20)

Cites Work

• Unnamed Item
• Sieve bootstrap for smoothing in nonstationary time series
• Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
• A bootstrap theory for weakly integrated processes
• Time series properties of ARCH processes with persistent covariates
• Tests for \(m\)-dependence based on sample splitting methods
• ARCH/GARCH with persistent covariate: asymptotic theory of MLE
• Asymptotics for linear processes
• COVARIANCE-BASED ORTHOGONALITY TESTS FOR REGRESSORS WITH UNKNOWN PERSISTENCE

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