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Econometrica Vol. 81 No. 4 2013

Robust Estimation and Inference for Jumps in Noisy High Frequency Data: A Local-to-Continuity Theory for the Pre-Averaging Method

Jia Li1,2

1 RELX Group (Netherlands) · 2 Duke University

Abstract

We develop an asymptotic theory for the pre-averaging estimator when asset price jumps are weakly identified, here modeled as local to zero. The theory unifies the conventional asymptotic theory for continuous and discontinuous semimartingales as two polar cases with a continuum of local asymptotics, and explains the breakdown of the conventional procedures under weak identification. We propose simple bias-corrected estimators for jump power variations, and construct robust confidence sets with valid asymptotic size in a uniform sense. The method is also robust to certain forms of microstructure noise.

DOI
10.3982/ecta10534
Volume
81
Issue
4
Pages
1673-1693
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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