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HYPOTHESIS TESTING FOR ARCH MODELS: A MULTIPLE QUANTILE REGRESSIONS APPROACH
Author(s) -
Kim Seonjin
Publication year - 2015
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/jtsa.12089
Subject(s) - heteroscedasticity , quantile , mathematics , quantile regression , statistics , test statistic , estimator , econometrics , likelihood ratio test , autoregressive model , statistical hypothesis testing
We propose a quantile regression‐based test to detect the presence of autoregressive conditional heteroscedasticity by combining distributional information across multiple quantiles. A chi‐square‐type test statistic based on the weighted average of distinct regression quantile estimators is formed. Unlike the widely used likelihood‐based tests, the proposed test does not make any distributional assumptions on the underlying errors. Monte Carlo simulation studies show that the proposed test outperforms the likelihood‐based tests in several aspects.