Predictive quantile regressions under persistence and conditional heteroskedasticity

DOI10.1016/j.jeconom.2019.04.014zbMath1456.62188OpenAlexW2753244708WikidataQ128071742 ScholiaQ128071742MaRDI QIDQ2330756

Rui Fan, Ji Hyung Lee

Publication date: 23 October 2019

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

Full work available at URL: https://doi.org/10.1016/j.jeconom.2019.04.014

zbMATH Keywords

quantile regressionconditional heteroskedasticitypredictive regressionmoving block bootstrap\(\alpha\)-mixing process

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Linear regression; mixed models (62J05) Nonparametric statistical resampling methods (62G09)

Related Items (9)

COMPLETE SUBSET AVERAGING FOR QUANTILE REGRESSIONS ⋮ Nonparametric inference for quantile cointegrations with stationary covariates ⋮ Forecasting vector autoregressions with mixed roots in the vicinity of unity ⋮ Penetrating sporadic return predictability ⋮ Extensions to IVX methods of inference for return predictability ⋮ Predictive quantile regression with mixed roots and increasing dimensions: the ALQR approach ⋮ Robust inference with stochastic local unit root regressors in predictive regressions ⋮ QUANTILOGRAMS UNDER STRONG DEPENDENCE ⋮ A new robust inference for predictive quantile regression

Uses Software

• bootstrap

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Robust econometric inference with mixed integrated and mildly explosive regressors
• Quantile cointegrating regression
• Properties of a block bootstrap under long-range dependence
• The use of subseries values for estimating the variance of a general statistic from a stationary sequence
• Asymptotic behavior of regression quantiles in non-stationary, dependent cases
• The moving blocks bootstrap and robust inference for linear least squares and quantile regressions
• A perspective on recent methods on testing predictability of asset returns
• A smooth block bootstrap for quantile regression with time series
• Limiting distributions for \(L_1\) regression estimators under general conditions
• The jackknife and the bootstrap for general stationary observations
• Consistency of the jackknife-after-bootstrap variance estimator for the bootstrap quantiles of a Studentized statistic
• Predictive regression under various degrees of persistence and robust long-horizon regression
• Conditional Quantile Estimation for Generalized Autoregressive Conditional Heteroscedasticity Models
• Predicting the Equity Premium with Dividend Ratios
• Distribution of quantiles in samples from a bivariate population
• Approximation Theorems of Mathematical Statistics
• Continuous Time Approximations to GARCH and Stochastic Volatility Models
• Towards a unified asymptotic theory for autoregression
• Robust Tests for Heteroscedasticity Based on Regression Quantiles
• Regression Quantiles
• The Stationary Bootstrap
• MIXING AND MOMENT PROPERTIES OF VARIOUS GARCH AND STOCHASTIC VOLATILITY MODELS
• On blocking rules for the bootstrap with dependent data
• Nonlinear system theory: Another look at dependence
• Predictive quantile regression with persistent covariates: IVX-QR approach
• A reexamination of stock return predictability

This page was built for publication: Predictive quantile regressions under persistence and conditional heteroskedasticity