Department of Economics and Business Economics

An Econometric Analysis of Modulated Realised Covariance, Regression and Correlation in Noisy Diffusion Models

Research output: Working paperResearch

  • School of Economics and Management
This paper introduces a new estimator to measure the ex-post covariation between
high-frequency financial time series under market microstructure noise. We provide an
asymptotic limit theory (including feasible central limit theorems) for standard methods
such as regression, correlation analysis and covariance, for which we obtain the optimal rate
of convergence. We demonstrate some positive semidefinite estimators of the covariation
and construct a positive semidefinite estimator of the conditional covariance matrix in
the central limit theorem. Furthermore, we indicate how the assumptions on the noise
process can be relaxed and how our method can be applied to non-synchronous observations.
We also present an empirical study of how high-frequency correlations, regressions and
covariances change through time.
Original languageEnglish
Place of publicationAarhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages48
Publication statusPublished - 2008

    Research areas

  • Central Limit Theorem; Diffusion Models; Market Microstructure Noise; Non-synchronous Trading; High-Frequency Data; Semimartingale Theory

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ID: 11349088