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Multivariate Realised Kernels: Consistent Positive Semi-Definite Estimators of the Covariation of Equity Prices with Noise and Non-Synchronous Trading
Ole E. Barndorff-Nielsen Thiele Centre, Dept. Math. Sciences, Univ. Aarhus Peter Reinhard Hansen Stanford University; University of Aarhus - CREATES Asger Lunde University of Aarhus - School of Economics and Management; CREATES Neil Shephard University of Oxford - Oxford-Man Institute; University of Oxford - Nuffield College; University of Oxford - Oxford Financial Research Centre July 27, 2008 Abstract: We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement noise of certain types and can also handle non-synchronous trading. It is the first estimator which has these three properties which are all essential for empirical work in this area. We derive the large sample asymptotics of this estimator and assess its accuracy using a Monte Carlo study. We implement the estimator on some US equity data, comparing our results to previous work which has used returns measured over 5 or 10 minutes intervals. We show the new estimator is substantially more precise.
Keywords: HAC estimator, Long run variance estimator, Market frictions, Quadratic variation, Realised Variance JEL Classifications: C13, C32 Working Paper SeriesDate posted: July 02, 2008 ; Last revised: December 17, 2008Suggested CitationContact Information
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