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Activity Number: 467
Type: Invited
Date/Time: Wednesday, August 12, 2015 : 8:30 AM to 10:20 AM
Sponsor: IMS
Abstract #314398
Title: Assessment of Uncertainty in High-Frequency Data: The Observed Asymptotic Variance
Author(s): Per A. Mykland and Lan Zhang*
Companies: The University of Chicago and University of Illinois at Chicago
Keywords: consistency ; high frequency estimation ; irregular observation times ; microstructure noise ; observed information ; semimartingale
Abstract:

A main problem in the analysis of financial high frequency data is the setting of standard errors. This is because the finding of estimators of asymptotic variance (AVAR) is often harder than finding point estimators. This paper proposes an alternative and general solution to this problem, which we call Observed Asymptotic Variance. It is a general nonparametric method. The Observed AVAR work well in the presence of microstructure noise, and when observation times are irregular.

Authors who are presenting talks have a * after their name.

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