Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/79576
Authors: 
Bibinger, Markus
Winkelmann, Lars
Year of Publication: 
2013
Series/Report no.: 
SFB 649 Discussion Paper 2013-021
Abstract: 
We establish estimation methods to determine co-jumps in multivariate high-frequency data with nonsynchronous observations and market microstructure noise. The ex-post quadratic covariation of the signal part, which is modeled by an Itˆo-semimartingale, is estimated with a locally adaptive spectral approach. Locally adaptive thresholding allows to disentangle the co-jump and continuous part in quadratic covariation. Our estimation procedure implicitly renders spot (co-)variance estimators. We derive a feasible stable limit theorem for a truncated spectral estimator of integrated covariance. A test for common jumps is obtained with a wild bootstrap strategy. We give an explicit guideline how to implement the method and test the algorithm in Monte Carlo simulations. An empirical application to intra-day tick-data demonstrates the practical value of the approach.
Subjects: 
co-jumps
covolatility estimation
jump detection
microstructure noise
non-synchronous observations
quadratic covariation
spectral estimation
truncation
JEL: 
C14
G32
E58
Document Type: 
Working Paper

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