Nonparametric estimation of structural change points in volatility models for time series

DOI10.1016/j.jeconom.2004.02.008zbMath1335.62126OpenAlexW2163537640MaRDI QIDQ262749

Yoon K. Choi, Gongmeng Chen, Yong Zhou

Publication date: 30 March 2016

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

Full work available at URL: https://doi.org/10.1016/j.jeconom.2004.02.008

zbMATH Keywords

asymptotic propertiesleast squaresnonparametric estimationchange points in volatility

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Nonparametric estimation (62G05) Economic time series analysis (91B84) Stochastic models in economics (91B70)

Related Items (19)

Adaptive jump-preserving estimates in varying-coefficient models ⋮ Off-line testing for a changed segment in the sample variance ⋮ Spurious regression due to neglected of non-stationary volatility ⋮ Statistical inference for the shape parameter change-point estimator in negative associated gamma distribution ⋮ Nonparametric analysis of the Shenzhen stock market: the day of the week effect ⋮ Nonparametric semirecursive identification in a wide sense of strong mixing processes ⋮ Estimating change points in nonparametric time series regression models ⋮ Least Squares Volatility Change Point Estimation for Partially Observed Diffusion Processes ⋮ Monitoring Variance Change in Infinite Order Moving Average Processes and Nonstationary Autoregressive Processes ⋮ CUSUM Methods for Monitoring Structural Changes in Structural Equations ⋮ Change point estimators by local polynomial fits under a dependence assumption ⋮ Asymptotic distribution of the jump change-point estimator ⋮ Ratio tests for variance change in nonparametric regression ⋮ Statistical inference for semiparametric varying-coefficient partially linear models with error-prone linear covariates ⋮ Adaptive likelihood estimator of conditional variance function ⋮ Estimation for the change point of volatility in a stochastic differential equation ⋮ Least-squares change-point estimation for the telegraph process observed at discrete times ⋮ Testing for a Change of the Innovation Distribution in Nonparametric Autoregression: The Sequential Empirical Process Approach ⋮ Unstable volatility: the break-preserving local linear estimator

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