High Frequency Covariance Estimates with Noisy and Asynchronous Financial Data
Princeton University - Department of Economics; National Bureau of Economic Research (NBER)
Princeton University - Bendheim Center for Finance
University of Chicago - Booth School of Business
June 1, 2010
This paper 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 upon the marriage of the quasi-maximum likelihood estimator of the quadratic variation and the proposed Generalized Synchronization scheme. It is therefore not influenced by the Epps effect. Moreover, the estimation procedure is free of tuning parameters or bandwidths and readily implementable. The 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 global financial crisis in 2008, discovering the similarities and differences in their roles as key currencies in the global market.
Number of Pages in PDF File: 37
Keywords: Market microstructure noise, Covariance, Quasi-Maximum Likelihood Estimator, Refresh Time, Generalized Synchronization
JEL Classification: C13, C22working papers series
Date posted: June 28, 2010
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