Copula-based multivariate GARCH model with uncorrelated dependent errors

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MGARCH models: Trade-off between feasibility and flexibility (2018, methodology): “It is also of interest to compare the models considered in these paper with those based on copulas; see, for example, Patton (2006), Lee and Long (2009), So and Yeung (2014) and Creal and Tsay (in press).”
A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations (2011, methodology): “The numerical optimization problem is then separated into more manageable pieces; see the discussions in Patton (2006) and Lee and Long (2009) who have explored time-varying multivariate Gaussian copulas.”
Copula Methods for Forecasting Multivariate Time Series (2013, methodology): “…to study nancial contagion; Dearden, et al. (2008) and Bonhomme and Robin (2009) use copulas to model the dynamics in a panel of earnings data; Lee and Long (2009) use copulas to exibly model the uncorrelated residuals of a multivariate GARCH model; Patton (2009b), Dudley and Nimalendran…”
High-Dimensional Copula-Based Distributions with Mixed Frequency Data (2016, unknown): “Thus rather than directly modelling uncorrelated residuals et as we do, Lee and Long (2009) use wt and its covariance matrix to obtain uncorrelated residuals et = 1=2wt: In this model it is generally hard to interpret wt, and thus to motivate or explain choices of models for its marginal…”