Multivariate GARCH models: a survey - Bauwens - 2006 - Journal of Applied Econometrics -
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This paper provides a review of some recent theoretical results for time series models with
GARCH errors, and is directed towards practitioners. Starting with the simple ARCH model …

An accessible guide to the multivariate time series tools used in numerous real-world
applications Multivariate Time Series Analysis: With R and Financial Applications is the …

In this article we propose a new multivariate generalized autoregressive conditional
heteroscedasticity (MGARCH) model with time-varying correlations. We adopt the vech …

This article contains a review of multivariate GARCH models. Most common GARCH models
are presented and their properties considered. This also includes nonparametric and …

Diagnostic checking is an important step in the modeling process. But while the literature on
diagnostic checks is quite extensive and many texts on time series modeling are available, it …

Autoregressive Conditional Heteroskedastic (ARCH) processes are used in finance to
model asset price volatility over time. This book introduces both the theory and applications …

We propose a factor generalized autoregressive conditional heteroscedasticity (GARCH)
model and develop test procedures for checking the correctness of the number of factors …

We examine the residual‐based diagnostics for univariate and multivariate conditional
heteroscedasticity models. The tests are based on the parameter estimates of an …

A new portmanteau diagnostic test for vector autoregressive moving average (VARMA)
models that is based on the determinant of the standardized multivariate residual …