GENERALIZED AUTOREGRESSIVE SCORE MODELS WITH APPLICATIONS

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A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations (2011, unknown): “which is equivalent to the generalized autoregressive conditional heteroskedasticity (GARCH) model of Engle (1982) and Bollerslev (1986); the GARCH(1, 1) model is given by ft+1 = ω + α1y 2 t + β1ft with α1 = A1 and β1 = B1 −A1.”
Conditional Euro Area Sovereign Default Risk (2014, methodology): “…and the scaling matrix, the GAS model (5)–(6) encompasses a wide range of familiar models, including the (multivariate) GARCH model, the autoregressive conditional duration (ACD) model, and the multiplicative error model (MEM); see Creal, Koopman, and Lucas (2013) for more examples.”
Forecasting football match results in national league competitions using score-driven time series models (2019, methodology): “We consider the class of score-driven models by Creal et al. (2013) for capturing the dynamic behavior of a parameter or a selection of parameters.”
In-sample confidence bands and out-of-sample forecast bands for time-varying parameters in observation-driven models (2016, methodology): “For a given linear Gaussian state space model, the Kalman filter can be used to calculate conditional means and variances of unobserved time-varying parameters (or linear functions thereof) in a computationally efficient manner; see, for example, Durbin and Koopman [2012] for a detailed treatment. I”