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 pre-averaging 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. Quadratic Variation , MarketMicrostructure Noise , Pre-averaging , Sampling Schemes , Jumps
| Verfasserangaben: | Nikolaus HautschORCiDGND, Mark Podolskij |
|---|---|
| URN: | urn:nbn:de:hebis:30-75630 |
| Titel des übergeordneten Werkes (Deutsch): | Center for Financial Studies (Frankfurt am Main): CFS working paper series ; No. 2010,17 |
| Schriftenreihe (Bandnummer): | CFS working paper series (2010, 17) |
| Dokumentart: | Arbeitspapier |
| Sprache: | Englisch |
| Jahr der Fertigstellung: | 2010 |
| Jahr der Erstveröffentlichung: | 2010 |
| Veröffentlichende Institution: | Universitätsbibliothek Johann Christian Senckenberg |
| Datum der Freischaltung: | 04.09.2010 |
| Freies Schlagwort / Tag: | Jumps; MarketMicrostructure Noise; Pre-averaging; Quadratic Variation; Sampling Schemes |
| Ausgabe / Heft: | July 2010 |
| Seitenzahl: | 57 |
| HeBIS-PPN: | 226768503 |
| Institute: | Wirtschaftswissenschaften / Wirtschaftswissenschaften |
| DDC-Klassifikation: | 3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft |
| JEL-Klassifikation: | C Mathematical and Quantitative Methods / C1 Econometric and Statistical Methods: General / C14 Semiparametric and Nonparametric Methods |
| C Mathematical and Quantitative Methods / C2 Single Equation Models; Single Variables / C22 Time-Series Models; Dynamic Quantile Regressions (Updated!) | |
| Sammlungen: | Universitätspublikationen |
| Lizenz (Deutsch): |  Deutsches Urheberrecht |
