Forecasting for quantile self-exciting threshold autoregressive time series models

DOI10.1093/biomet/asp070zbMath1183.62158OpenAlexW2087651008MaRDI QIDQ5305481

Yuzhi Cai

Publication date: 22 March 2010

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1093/biomet/asp070

zbMATH Keywords

Monte Carlo methodforecasting methodquantile forecastpredictive density function

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Monte Carlo methods (65C05)

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Statistical inference for conditional quantiles in nonlinear time series models ⋮ Markov switching quantile autoregression ⋮ Single-index Thresholding in Quantile Regression ⋮ A new Bayesian approach to quantile autoregressive time series model estimation and forecasting ⋮ Combining Forecasts via Simulations ⋮ Semi-parametric quantile estimation for double threshold autoregressive models with heteroskedasticity ⋮ Quantile regression for thinning-based INAR(1) models of time series of counts ⋮ Quantile regression for dynamic panel data with fixed effects ⋮ Testing linearity against threshold effects: uniform inference in quantile regression ⋮ A quantile function approach to the distribution of financial returns following TGARCH models ⋮ Threshold quantile autoregressive models ⋮ Common threshold in quantile regressions with an application to pricing for reputation ⋮ Testing for a unit root in a nonlinear quantile autoregression framework

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