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Conditional Quantile Estimation and Inference for Arch Models

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.
Year of publication:
1996
Authors: Koenker, Roger ; Zhao, Quanshui
Published in:
Econometric Theory. - Cambridge University Press. - Vol. 12.1996, 05, p. 793-813
Publisher: Cambridge University Press
Description of contents: Abstract [journals.cambridge.org]
Type of publication: Article
Source:
Persistent link: https://www.econbiz.de/10005610574
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