Robust estimation and inference for jumps in noisy high frequency data: A local-to-continuity theory for the pre-averaging method


Journal Article

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. © 2013 The Econometric Society.

Full Text

Duke Authors

Cited Authors

  • Li, J

Published Date

  • July 1, 2013

Published In

Volume / Issue

  • 81 / 4

Start / End Page

  • 1673 - 1693

Electronic International Standard Serial Number (EISSN)

  • 1468-0262

International Standard Serial Number (ISSN)

  • 0012-9682

Digital Object Identifier (DOI)

  • 10.3982/ECTA10534

Citation Source

  • Scopus