Arbeitspapier

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

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
URN
urn:nbn:de:hebis:30-75630
Last update
10.03.2025, 11:45 AM CET

Data provider

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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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