Multivariate GARCH models: a survey - Bauwens - 2006 - Journal of Applied Econometrics -
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Time series econometrics is a rapidly evolving field. Particularly, the cointegration revolution
has had a substantial impact on applied analysis. Hence, no textbook has managed to cover …

This book contains a up-to-date overview of nonlinear time series models and their
application to modelling economic relationships. It considers nonlinear models in stationary …

Quasi maximum likelihood estimation and inference in multivariate volatility models remains
a challenging computational task if, for example, the dimension of the parameter space is …

The Gaussian quasi-maximum likelihood estimator of Multivariate GARCH models is shown
to be very sensitive to outliers in the data. A class of robust M-estimators for MGARCH …

We apply the multivariate extension of GARCH-type models in order to assess the
systematic and systemic risks as well as the joint volatility behaviors of the US and three …

The recent growth and development of aquaculture industry in Bangladesh demand a
thorough investigation of price volatility spillover pattern among capture fisheries and …

The Doubly Adaptive LASSO Methods for Time Series Analysis Page 1 Western University
Scholarship@Western Electronic Thesis and Dissertation Repository 8-22-2014 12:00 AM The …

In this paper, sequential procedures for the surveillance of the covariance matrices of
multivariate nonlinear time series are introduced. Two different types of control charts are …

We extend the full-factor multivariate GARCH model of Vrontos et al.(Econom J 6: 312–334,
2003a) to account for fat tails in the conditional distribution of financial returns, using a …