Department of Economics and Business Economics

Subsampling Realised Kernels

Publication: Research - peer-reviewJournal article

In a recent paper we have introduced the class of realised kernel estimators of the increments of quadratic variation in the presence of noise. We showed that this estimator is consistent and derived its limit distribution under various assumptions on the kernel weights. In this paper we extend our analysis, looking at the class of subsampled realised kernels and we derive the limit theory for this class of estimators. We find that subsampling is highly advantageous for estimators based on discontinuous kernels, such as the truncated kernel. For kinked kernels, such as the Bartlett kernel, we show that subsampling is impotent, in the sense that subsampling has no effect on the asymptotic distribution. Perhaps surprisingly, for the efficient smooth kernels, such as the Parzen kernel, we show that subsampling is harmful as it increases the asymptotic variance. We also study the performance of subsampled realised kernels in simulations and in empirical work.
Original languageEnglish
JournalJournal of Econometrics
Volume160
Issue number1
Pages (from-to)204-219
Number of pages16
ISSN0304-4076
DOIs
StatePublished - 2011

See relations at Aarhus University Citationformats

ID: 22883155