Testing and Modelling for the Structural Change in Covariance Matrix Time Series With Multiplicative Form

DOI10.5705/ss.202021.0029OpenAlexW4200520739WikidataQ114013800 ScholiaQ114013800MaRDI QIDQ6086165

Feiyu Jiang, Ke Zhu, Dong Li, Wai Keung Li

Publication date: 9 November 2023

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.5705/ss.202021.0029

zbMATH Keywords

realized covariance matrixsemiparametric time series modelcovariance matrix time series modelprofiled quasi maximum likelihood estimationstructural change testing

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Unnamed Item
• Unnamed Item
• Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
• Adaptive estimation of autoregressive models with time-varying variances
• The Wishart autoregressive process of multivariate stochastic volatility
• A specification test for nonlinear nonstationary models
• Testing for unit roots in time series models with non-stationary volatility
• Adaptive estimation of vector autoregressive models with time-varying variance: application to testing linear causality in mean
• Testing structural change in time-series nonparametric regression models
• Inference of time-varying regression models
• Efficient estimation of a multivariate multiplicative volatility model
• The conditional autoregressive Wishart model for multivariate stock market volatility
• On asymptotic theory for multivariate GARCH models
• Break detection in the covariance structure of multivariate time series models
• A note on estimating eigenvalues of scale matrix of the multivariate \(F\)- distribution
• Comparing nonparametric versus parametric regression fits
• Testing the constancy of regression parameters against continuous structural change
• Fitting time series models to nonstationary processes
• Testing for structural change in conditional models
• Factor models for matrix-valued high-dimensional time series
• Testing for parameter constancy in GARCH\((p,q)\) models
• The jackknife and the bootstrap for general stationary observations
• Testing for a change in the parameter values and order of an autoregressive model
• A model-free consistent test for structural change in regression possibly with endogeneity
• Adaptive inference for a semiparametric generalized autoregressive conditional heteroskedasticity model
• Statistical inference for autoregressive models under heteroscedasticity of unknown form
• Nonlinear regressions with nonstationary time series
• Modeling and testing smooth structural changes with endogenous regressors
• Structural breaks in time series
• Testing for Smooth Structural Changes in Time Series Models via Nonparametric Regression
• Large Volatility Matrix Inference via Combining Low-Frequency and High-Frequency Approaches
• Tests for Parameter Instability and Structural Change With Unknown Change Point
• TESTING FOR STRUCTURAL CHANGE IN TIME-VARYING NONPARAMETRIC REGRESSION MODELS
• A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
• Automatic Block-Length Selection for the Dependent Bootstrap
• Estimating and Testing Linear Models with Multiple Structural Changes
• Kernel-Based Semiparametric Estimators: Small Bandwidth Asymptotics and Bootstrap Consistency
• Simultaneous Inference of Linear Models with Time Varying Coefficients
• TESTING STRICT STATIONARITY WITH APPLICATIONS TO MACROECONOMIC TIME SERIES
• Sparse Matrix Graphical Models
• SIMULTANEOUSLY MODELING CONDITIONAL HETEROSKEDASTICITY AND SCALE CHANGE
• Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models
• Time series models for realized covariance matrices based on the matrix-F distribution
• Two‐Step Estimation for Time Varying Arch Models
• Testing for Change Points in Time Series
• Estimating and Testing Structural Changes in Multivariate Regressions
• Modeling and Forecasting Realized Volatility
• Econometric Analysis of Realized Covariation: High Frequency Based Covariance, Regression, and Correlation in Financial Economics
• Twicing Kernels and a Small Bias Property of Semiparametric Estimators
• DETECTING FOR SMOOTH STRUCTURAL CHANGES IN GARCH MODELS
• Multiple-Change-Point Detection for Auto-Regressive Conditional Heteroscedastic Processes