Statistical inference for conditional quantiles in nonlinear time series models

DOI10.1016/J.JECONOM.2015.03.037zbMath1337.62280OpenAlexW3125060511MaRDI QIDQ888341

Ray S. W. Chung, Mike K. P. So

Publication date: 30 October 2015

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

Full work available at URL: https://doi.org/10.1016/j.jeconom.2015.03.037

zbMATH Keywords

conditional quantilenonlinear time seriesspecification testhigh-end quantile estimation

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05)

Related Items (7)

Stochastic tail index model for high frequency financial data with Bayesian analysis ⋮ Estimation and test for quantile nonlinear cointegrating regression ⋮ Frontiers in time series and financial econometrics: an overview ⋮ Quantile Co-Movement in Financial Markets: A Panel Quantile Model With Unobserved Heterogeneity ⋮ A quantile function approach to the distribution of financial returns following TGARCH models ⋮ Quasi‐maximum likelihood estimation of conditional autoregressive Wishart models ⋮ Hybrid quantile estimation for asymmetric power GARCH models

Uses Software

• CAViaR

Cites Work

• Confidence regions for high quantiles of a heavy tailed distribution
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• Conditional Quantile Estimation for Generalized Autoregressive Conditional Heteroscedasticity Models
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• On Bayesian Modeling of Fat Tails and Skewness
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances
• ESTIMATION OF A DENSITY FUNCTION USING ORDER STATISTICS1
• Regression Quantiles
• Consistency and Asymptotic Normality of the Quasi-Maximum Likelihood Estimator in IGARCH(1,1) and Covariance Stationary GARCH(1,1) Models
• Forecasting for quantile self-exciting threshold autoregressive time series models
• Inference in Arch and Garch Models with Heavy-Tailed Errors
• Weighted least absolute deviations estimation for an AR(1) process with ARCH(1) errors
• Quantile Autoregression
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