Spatial Autoregressive Conditional Heteroskedasticity Models
نویسندگان
چکیده
منابع مشابه
Generalized Autoregressive Conditional Heteroskedasticity
A natural generalization of the ARCH (Autoregressive Conditional Heteroskedastic) process introduced in Engle (1982) to allow for past conditional variances in the current conditional variance equation is proposed. Stationarity conditions and autocorrelation structure for this new class of parametric models are derived. Maximum likelihood estimation and testing are also considered. Finally an e...
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where $‘s inre r*onst,ant matricaes; detI{@(z)} = 11 @,x . w * $JP[ = 0 has ci 5 771, urrit roots and ‘I’ = 711 d roots omside the urrit, circle: tPt = ((1 it, 7 c+> is a sequcnce of independent1 and idcntically distlributled (i.i.tl) matrices with mean zero and nonnegativc covarianc~e IC[ /le+&) ~f’(&)] = 0; pit is an i.i.d ramlom vector witIh mean zero and positive covariance E ( etef j = CA ...
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Daily returns of nancial assets are frequently found to exhibit positive autocor-relation at lag 1. When specifying a linear AR(1) conditional mean, one may ask how this predictability aaects option prices. We investigate the dependence of option prices on autoregressive dynamics under stylized facts of stock returns, i.e., conditional heteroskedasticity, leverage eeect, and conditional leptoku...
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ژورنال
عنوان ژورنال: JOURNAL OF THE JAPAN STATISTICAL SOCIETY
سال: 2017
ISSN: 1348-6365,1882-2754
DOI: 10.14490/jjss.47.221