A Hausman test for the presence of market microstructure noise in high frequency data

Yacine Ait-Sahalia, Dacheng Xiu

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

We develop tests that help assess whether a high frequency data sample can be treated as reasonably free of market microstructure noise at a given sampling frequency for the purpose of implementing high frequency volatility and other estimators. The tests are based on the Hausman principle of comparing two estimators, one that is efficient but not robust to the deviation being tested, and one that is robust but not as efficient. We investigate the asymptotic properties of the test statistic in a general nonparametric setting, and compare it with several alternatives that are also developed in the paper. Empirically, we find that improvements in stock market liquidity over the past decade have increased the frequency at which simple, uncorrected, volatility estimators can be safely employed.

Original languageEnglish (US)
Pages (from-to)176-205
Number of pages30
JournalJournal of Econometrics
Volume211
Issue number1
DOIs
StatePublished - Jul 1 2019

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

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