Modelling Multivariate Volatilities via Conditionally Uncorrelated Components

DOI10.1111/j.1467-9868.2008.00654.xOpenAlexW2006875428MaRDI QIDQ3631467

Qiwei Yao, Mingjin Wang, Jianqing Fan

Publication date: 10 June 2009

Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/math/0506027

zbMATH Keywords

time seriesdimension reductionbootstrap testfinancial returnscausality in variancequasi-maximum-likelihood estimatorextended GARCH(1, 1) modelportfolio volatility

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items

Multivariate GARCH estimation via a Bregman-proximal trust-region method, Efficient factor GARCH models and factor-DCC models, Weighted scatter estimation method of the GO-GARCH models, Bayesian inference of multivariate rotated GARCH models with skew returns, Dynamic conditional eigenvalue GARCH, Determining the number of factors in a multivariate error correction-volatility factor model, Asymptotics of Cholesky GARCH models and time-varying conditional betas, Stable mixture GARCH models, Principal component analysis for second-order stationary vector time series, Estimating and forecasting dynamic correlation matrices: a nonlinear common factor approach, Multivariate rotated ARCH models, Method of moments estimation of GO-GARCH models, Modeling temporally uncorrelated components of complex-valued stationary processes, Regularization for stationary multivariate time series

Uses Software

• FinTS

Cites Work

• Unnamed Item
• Regime switching for dynamic correlations
• Minimum volume sets and generalized quantile processes
• Central limit theorems for empirical and \(U\)-processes of stationary mixing sequences
• Rates of convergence for empirical processes of stationary mixing sequences
• Nonlinear time series. Nonparametric and parametric methods
• Weak convergence and empirical processes. With applications to statistics
• A causality-in-variance test and its application to financial market prices
• A Lagrange multiplier test for causality in variance
• Bootstrap and wild bootstrap for high dimensional linear models
• Estimation in conditionally heteroscedatic time series models.
• Least absolute deviations estimation for ARCH and GARCH models
• DIAGNOSTIC CHECKING ARMA TIME SERIES MODELS USING SQUARED-RESIDUAL AUTOCORRELATIONS
• Modeling Multiple Times Series with Applications
• Multivariate Stochastic Variance Models
• A Note on Diagnosing Multivariate Conditional Heteroscedasticity Models