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Minimum Distance Estimation of GARCH(1,1) models
No full textA distribution free approach to the estimation of GARCH(1, 1) models is presented. More specifically, the proposed method
relies on a Minimum Distance Estimator (MDE) based on the autocovariance function of the squared observations. The asymptotic
properties of the estimator are studied giving conditions for its consistency and asymptotic normality while its finite sample efficiency
is assessed by means of a simulation study. Finally the proposed estimation method is applied to a time series of hourly returns on
the FTSE100 index futures
Modelling asymmetric volatility dynamics by multivariate BL-GARCH models
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Modelli Autoregressivi con Coefficienti Stocastici ed Effetti Asimmetrici nella Volatilità dei Rendimenti Azionari
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