Template-type: ReDIF-Paper 1.0
Author-Name: Ole E. Barndorff-Nielsen
Author-Workplace-Name: University of Aarhus
Author-Name: Peter Reinhard Hansen
Author-Workplace-Name: Stanford University
Author-Name: Asger Lunde
Author-Workplace-Name: Aarhus School of Business
Author-Name: Neil Shephard
Author-Email: neil.shephard@nuffield.ox.ac.uk
Author-Workplace-Name: Nuffield College, University of Oxford
Title: Regular and Modified Kernel-Based Estimators of Integrated Variance: 
The Case with Independent Noise 
Abstract: We consider kernel-based estimators of integrated variances in
the presence of independent market microstructure effects. We 
derive the bias and variance properties for all regular
kernel-based estimators and derive a lower bound for their
asymptotic variance. Further we show that the subsample-based
estimator is closely related to a Bartlett-type kernel
estimator. The small difference between the two estimators due
to end effects, turns out to be key for the consistency of the
subsampling estimator. This observation leads us to a modified
class of kernel-based estimators, which are also consistent. We
study the efficiency of our new kernel-based procedure. We show
that optimal modified kernel-based estimator converges to the
integrated variance at the optimal rate, m^1/4, where m is the
number of intraday returns.
Length: 42 pages
Creation-Date:2004-11-15
Number:2004-W28
File-URL: http://www.nuff.ox.ac.uk/economics/papers/2004/w28/RVkernel10.pdf
File-Format: application/pdf
Handle: RePEc:nuf:econwp:0428