Arbeitspapier

Pre-averaging based estimation of quadratic variation in the presence of noise and jumps: Theory, implementation, and empirical evidence

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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.

Language: Englisch

Bibliographic citation: Series: CFS Working Paper ; No. 2010/17

Classification: Wirtschaft
Semiparametric and Nonparametric Methods: General
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
General Financial Markets: General (includes Measurement and Data)

Subject: Quadratic Variation
MarketMicrostructure Noise
Pre-averaging
Sampling Schemes
Jumps

Event: Geistige Schöpfung

(who): Hautsch, Nikolaus
Podolskij, Mark

Event: Veröffentlichung

(who): Goethe University Frankfurt, Center for Financial Studies (CFS)

(where): Frankfurt a. M.

(when): 2010

Handle: http://hdl.handle.net/10419/43201

URN: urn:nbn:de:hebis:30-75630

Last update: 10.03.2025, 11:45 AM CET

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Object type

Arbeitspapier

Associated

Hautsch, Nikolaus
Podolskij, Mark
Goethe University Frankfurt, Center for Financial Studies (CFS)

Time of origin

2010

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