Subsampling realised kernels

Ole Barndorff-Nielsen, Peter Hansen, Asger Lunde () and Neil Shephard ()

Journal of Econometrics, 2011, vol. 160, issue 1, 204-219

Abstract: 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.

Keywords: Long; run; variance; estimator; Market; frictions; Quadratic; variation; Realised; kernel; Realised; variance; Subsampling (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (41)

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Related works:
Working Paper: Subsampling realised kernels (2006)
Working Paper: Subsampling realised kernels (2006)
Working Paper: Subsampling realised kernels (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:160:y:2011:i:1:p:204-219

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