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Recursive modelling of symmetric and asymmetric volatility in the presence of extreme observations

✍ Scribed by Hock Guan Ng; Michael McAleer


Book ID
114174801
Publisher
Elsevier Science
Year
2004
Tongue
English
Weight
591 KB
Volume
20
Category
Article
ISSN
0169-2070

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The main contribution of this paper is a recursive algorithm for parametric system identification in the presence of both noise and model uncertainties. The estimates provided by this algorithm are not invalidated, after a learning period, by the observed input-output data and the assumed system and