Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/43201 
Year of Publication: 
2010
Series/Report no.: 
CFS Working Paper No. 2010/17
Publisher: 
Goethe University Frankfurt, Center for Financial Studies (CFS), Frankfurt a. M.
Abstract: 
This paper provides theory as well as empirical results for pre-averaging estimators of the daily quadratic variation of asset prices. We derive jump robust inference for pre-averaging estimators, corresponding feasible central limit theorems and an explicit test on serial dependence in microstructure noise. Using transaction data of different stocks traded at the NYSE, we analyze the estimators' sensitivity to the choice of the pre-averaging bandwidth and suggest an optimal interval length. Moreover, we investigate the dependence of preaveraging based inference on the sampling scheme, the sampling frequency, microstructure noise properties as well as the occurrence of jumps. As a result of a detailed empirical study we provide guidance for optimal implementation of pre-averaging estimators and discuss potential pitfalls in practice.
Subjects: 
Quadratic Variation
MarketMicrostructure Noise
Pre-averaging
Sampling Schemes
Jumps
JEL: 
C14
C22
G10
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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