High-frequency covariance estimates with noisy and asynchronous financial data

Research output: Contribution to journalArticlepeer-review

168 Scopus citations


This article proposes a consistent and efficient estimator of the high-frequency covariance (quadratic covariation) of two arbitrary assets, observed asynchronously with market microstructure noise. This estimator is built on the marriage of the quasi-maximum likelihood estimator of the quadratic variation and the proposed generalized synchronization scheme and thus is not influenced by the Epps effect. Moreover, the estimation procedure is free of tuning parameters or bandwidths and is readily implementable. Monte Carlo simulations show the advantage of this estimator by comparing it with a variety of estimators with specific synchronization methods. The empirical studies of six foreign exchange future contracts illustrate the time-varying correlations of the currencies during the 2008 global financial crisis, demonstrating the similarities and differences in their roles as key currencies in the global market.

Original languageEnglish (US)
Pages (from-to)1504-1517
Number of pages14
JournalJournal of the American Statistical Association
Issue number492
StatePublished - Dec 2010

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


  • Covariance
  • Generalized synchronization method
  • Market microstructure noise
  • Quasi-maximum likelihood estimator
  • Refresh time


Dive into the research topics of 'High-frequency covariance estimates with noisy and asynchronous financial data'. Together they form a unique fingerprint.

Cite this