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ON THE PARAMETRIZATION OF MULTIVARIATE GARCH MODELS
Econometric Theory, 2007This paper deals with issues of structure and parametrization of VECH models proposed in Bollerslev, Engle, and Wooldridge (1988) and Baba, Engle, Kraft, and Kroner (BEKK) models. Both general models and also restricted versions such as the widely used diagonal VECH (DVECH) and factor generalized autoregressive conditional heteroskedastic (F-GARCH ...
Wolfgang Scherrer, Eva Ribarits
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GO‐GARCH: a multivariate generalized orthogonal GARCH model
Journal of Applied Econometrics, 2002AbstractMultivariate GARCH specifications are typically determined by means of practical considerations such as the ease of estimation, which often results in a serious loss of generality. A new type of multivariate GARCH model is proposed, in which potentially large covariance matrices can be parameterized with a fairly large degree of freedom while ...
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A multivariate GARCH–jump mixture model
Journal of Forecasting, 2023AbstractThis paper proposes a new parsimonious multivariate GARCH–jump (MGARCH–jump) mixture model with multivariate jumps that allows both jump sizes and jump arrivals to be correlated among assets. Dependent jumps impact the conditional moments of returns and beta dynamics of a stock. Applied to daily stock returns, the model identifies co‐jumps well
Chenxing Li, John M. Maheu
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Multivariate
ABSTRACTA new clustered correlation multivariate generalized autoregressive conditional heteroskedasticity (CC‐MGARCH) model that allows conditional correlations to form clusters is proposed. This model generalizes the time‐varying correlation structure of Tse and Tsui (2002, Journal of Business and Economic Statistics 20: 351–361) by classifying the ...
So, Mike K.P., Yip, Iris W.H.
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REALIZED BETA GARCH: A MULTIVARIATE GARCH MODEL WITH REALIZED MEASURES OF VOLATILITY
Journal of Applied Econometrics, 2014SUMMARYWe introduce a multivariate generalized autoregressive conditional heteroskedasticity (GARCH) model that incorporates realized measures of variances and covariances. Realized measures extract information about the current levels of volatilities and correlations from high‐frequency data, which is particularly useful for modeling financial returns
HANSEN, Peter Reinhard +2 more
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A Student-T Full Factor Multivariate GARCH Model
SSRN Electronic Journal, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Diamantopoulos, K., Vrontos, I. D.
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Multivariate ARCH and GARCH Models
2005In the previous chapters, we have discussed modelling the conditional mean of the data generation process of a multiple time series, conditional on the past at each particular time point. In that context, the variance or covariance matrix of the conditional distribution was assumed to be time invariant. In fact, in much of the discussion, the residuals
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Testing multivariate distributions in GARCH models
Journal of Econometrics, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bai, Jushan, Chen, Zhihong
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Multivariate GARCH models for large-scale applications: A survey
2019This chapter provides a survey of various multivariate GARCH specifications that model the temporal dependence in the second moment of multivariate return series processes. The survey is focused on feasible multivariate GARCH models for large-scale applications, as well as on recent contributions in outlier-robust MGARCH analysis and the use of high ...
Boudt, Kris +3 more
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A full-factor multivariate GARCH model
Econometrics Journal, 2003Summary: A new multivariate time series model with time varying conditional variances and covariances is presented and analysed. A complete analysis of the proposed model is presented consisting of parameter estimation, model selection and volatility prediction. Classical and Bayesian techniques are used for the estimation of the model parameters.
Vrontos, I. D. +2 more
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