Conditional quantile estimation and inference for ARCH models

被引：167

作者：

Koenker, R ^{[1
]}

Zhao, QS ^{[1
]}

机构：

[1] CITY UNIV HONG KONG,HONG KONG,HONG KONG

来源：

ECONOMETRIC THEORY | 1996年 / 12卷 / 05期

关键词：

D O I：

10.1017/S0266466600007167

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

Quantile regression methods are suggested for a class of ARCH models. Because conditional quantiles are readily interpretable in semiparametric ARCH models and are inherently 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.

引用

页码：793 / 813

页数：21

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