Abstract
This article discusses the asymptotic and finite-sample properties of the CUSUM tests for detecting structural breaks in volatility when the data are perturbed with (additive) outliers and/or measurement errors. The special focus is on the parametric and non-parametric tests in Inclan and Tiao (1994) and Kokoszka and Leipus (2000). Whereas the asymptotic distribution of the former can be largely affected, the distribution of the latter remains invariant and renders consistent break-point estimates. In small samples, however, large additive outliers are able to generate sizeable distortions in both tests, which explains some of the contradictory findings in previous literature.
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