QUASI-MAXIMUM LIKELIHOOD ESTIMATION OF SEMI-STRONG GARCH MODELS

By Juan-Carlos Escanciano. Econometric Theory, 2009

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NONPARAMETRIC ESTIMATION OF CONDITIONAL VALUE-AT-RISK AND EXPECTED SHORTFALL BASED ON EXTREME VALUE THEORY (2016, background): “, Drost and Nijman (1993), Escanciano (2009), and Linton, Pan, and Wang (2010).”
QML INFERENCE FOR VOLATILITY MODELS WITH COVARIATES (2015, methodology): “…is no covariate (r = 0), we retrieve the results obtained by Francq and Zakoı̈an (2004) in the GARCH case (δ0 = 2 and α0i+ = α0i−) and when (ηt ) is iid, by Escanciano (2009) in the GARCH case when (ηt ) is a conditionally homoscedastic martingale difference, and by HZ in the general APARCH case.”
Optimal predictions of powers of conditionally heteroscedastic processes (2013, methodology): “1 The standard GARCH(p, q) case To our knowledge, the mildest assumptions for the √ n consistency and AN of the gaussian QMLE for standard GARCH with iid errors were obtained by Berkes, Horváth and Kokoszka (2003) and Francq and Zakoïan (2004) (see Escanciano (2009) for an extension to martingale di”
PARAMETER ESTIMATION IN NONLINEAR AR–GARCH MODELS (2011, unknown): “Previously, conditions similar to Assumption E have been employed by Lee and Hansen (1994) and Escanciano (2009) to develop estimation theory for linear GARCH models (see also Linton, Pan, and Wang (in press)). We now discuss sufficient conditions for Assumption DGP. Such conditions were recently ob”
GARCH Models (2010, unknown): “An extension to non-iid errors was recently proposed by Escanciano (2009).”