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On estimation in conditionally heteroskedastic time series models under non-normal distributions
by
S. Liu
Australian National University
Coauthors: Professor C.C. Heyde (Australian National University/Columbia University)
Financial time series data are observed with heavy tails and time-varying volatility. Conditionally heteroskedastic models have then been received considerable attention. Our purpose is to examine some of these models in a general setting under some non-normal distributions. A likelihood based approach to estimation is used. New comparisons of estimators and their efficiencies will be discussed.
Date received: April 4, 2002
Copyright © 2002 by the author(s). The author(s) of this document and the organizers of the conference have granted their consent to include this abstract in Atlas Conferences Inc. Document # cajg-02.