Edgeworth expansion for the pre-averaging estimator

Mark Podolskij, Bezirgen Veliyev and Nakahiro Yoshida

Stochastic Processes and their Applications, 2017, vol. 127, issue 11, 3558-3595

Abstract: In this paper, we study the Edgeworth expansion for a pre-averaging estimator of quadratic variation in the framework of continuous diffusion models observed with noise. More specifically, we obtain a second order expansion for the joint density of the estimators of quadratic variation and its asymptotic variance. Our approach is based on martingale embedding, Malliavin calculus and stable central limit theorems for continuous diffusions. Moreover, we derive the density expansion for the studentized statistic, which might be applied to construct asymptotic confidence regions.

Keywords: Diffusion processes; Edgeworth expansion; high frequency observations; quadratic variation; pre-averaging (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (5)

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Related works:
Working Paper: Edgeworth expansion for the pre-averaging estimator (2015)
Working Paper: Edgeworth expansion for the pre-averaging estimator (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:spapps:v:127:y:2017:i:11:p:3558-3595

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DOI: 10.1016/j.spa.2017.03.001

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