Arbeitspapier
Jump-robust volatility estimation using nearest neighbor truncation
We propose two new jump-robust estimators of integrated variance based on highfrequency return observations. These MinRV and MedRV estimators provide an attractive alternative to the prevailing bipower and multipower variation measures. Specifically, the MedRV estimator has better theoretical efficiency properties than the tripower variation measure and displays better finite-sample robustness to both jumps and the occurrence of 'zero' returns in the sample. Unlike the bipower variation measure, the new estimators allow for the development of an asymptotic limit theory in the presence of jumps. Finally, they retain the local nature associated with the low-order multipower variation measures. This proves essential for alleviating finite sample biases arising from the pronounced intraday volatility pattern that afflicts alternative jump-robust estimators based on longer blocks of returns. An empirical investigation of the Dow Jones 30 stocks and an extensive simulation study corroborate the robustness and efficiency properties of the new estimators.
- Language
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Englisch
- Bibliographic citation
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Series: Staff Report ; No. 465
- Classification
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Wirtschaft
Semiparametric and Nonparametric Methods: General
Statistical Simulation Methods: General
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Data Collection and Data Estimation Methodology; Computer Programs: General
General Financial Markets: General (includes Measurement and Data)
- Subject
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Integrated volatility
jump robust
- Event
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Geistige Schöpfung
- (who)
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Andersen, Torben G.
Dobrev, Dobrislav
Schaumburg, Ernst
- Event
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Veröffentlichung
- (who)
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Federal Reserve Bank of New York
- (where)
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New York, NY
- (when)
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2010
- Handle
- Last update
-
10.03.2025, 11:44 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Andersen, Torben G.
- Dobrev, Dobrislav
- Schaumburg, Ernst
- Federal Reserve Bank of New York
Time of origin
- 2010
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Quantization to speedup approximate nearest neighbor search
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