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Conditional Quantile Estimation and Inference for Arch Models Author info | Abstract | Publisher info | Download info | Related research | Statistics Koenker, Roger
Zhao, Quanshui
Quantile regression methods are suggested for a class of ARCH models. Because conditional quantiles are readily interpretable in semiparametric ARCH models and are inherendy easier to estimate robustly than population moments, they offer some advantages over more familiar methods based on Gaussian likelihoods. Related inference methods, including the construction of prediction intervals, are also briefly discussed.
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Article provided by Cambridge University Press in its journal Econometric Theory .
Volume (Year): 12 (1996)
Issue (Month): 05 (December)
Pages: 793-813
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Handle: RePEc:cup:etheor:v:12:y:1996:i:05:p:793-813_00Contact details of provider: Postal: The Edinburgh Building, Shaftesbury Road, Cambridge CB2 2RU UK Fax: +44 (0)1223 325150 Email: Web page: http://journals.cambridge.org/jid_ECT
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