Beta-t-(E)GARCH

88 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Long Memory Dynamics for Multivariate Dependence under Heavy Tails (2014, methodology): “A similar model was developed by Harvey and Chakravarty (2008) and is referred to as the Beta-t-EGARCH model.”
Continuous Invertibility and Stable QML Estimation of the EGARCH(1,1) Model (2012, methodology): “ty are not proved except in the degenerate case 0 = 0 in [30]. On the contrary with other GARCH models, the QML estimation procedure is not always reliable for the EGARCH model, see the discussion in [19]. Thus, other estimation procedure has been investigated such as the bayesian, bias correction a”
A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations (2011, methodology): “Similar univariate models have been derived by, among others, Nelson and Foster (1994) and Harvey and Chakravarty (2008).”
GENERALIZED AUTOREGRESSIVE SCORE MODELS WITH APPLICATIONS (2013, methodology): “In independent work, a similar variance updating equation as (8) for the univariate Student’s t distribution is proposed by Harvey and Chakravarty (2008); they also discuss the properties of the model in more detail.”