Full Citation
Title: Parameter Estimation in Conditional Heteroscedastic Models
Citation Type: Journal Article
Publication Year: 2003
ISBN:
ISSN: 0361-0926
DOI: 10.1081/STA-120021324
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Abstract: Abstract We study asymptotics of parameter estimates in conditional heteroscedastic models. The estimators considered are those obtained by minimizing certain functionals and those obtained by solving estimation equations. We establish consistency and derive asymptotic limit laws of the estimators. Condition under which the limit law is normal is studied. Further, bootstrap for these estimators is discussed. The limiting distribution of the estimators is not necessary always normal, and we present a real data example to illustrate this.
Url: http://www.tandfonline.com/doi/abs/10.1081/STA-120021324
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Authors: Chatterjee, Snigdhansu; Das, Samarjit
Periodical (Full): Communications in Statistics - Theory and Methods
Issue: 6
Volume: 32
Pages: 1135-1153
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