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.
- Sprache
-
Englisch
- Erschienen in
-
Series: Staff Report ; No. 465
- Klassifikation
-
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)
- Thema
-
Integrated volatility
jump robust
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Andersen, Torben G.
Dobrev, Dobrislav
Schaumburg, Ernst
- Ereignis
-
Veröffentlichung
- (wer)
-
Federal Reserve Bank of New York
- (wo)
-
New York, NY
- (wann)
-
2010
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Andersen, Torben G.
- Dobrev, Dobrislav
- Schaumburg, Ernst
- Federal Reserve Bank of New York
Entstanden
- 2010
Ähnliche Objekte (12)
Heterogeneous autoregressive model with structural break using nearest neighbor truncation volatility estimators for DAX
Föderierte Nearest-Neighbor-Queries
Bias in nearest-neighbor hazard estimation
Bias in nearest-neighbor hazard estimation
On the risk of nearest neighbor rules
Nearest neighbor imputation algorithms: a critical evaluation
Quantization to speedup approximate nearest neighbor search
Kinetic Models for Topological Nearest-Neighbor Interactions
Optimized Nearest-Neighbor Classifiers Using Generated Instances
Efficient nearest neighbor search on metric time series
Weighted k-nearest-neighbor techniques and ordinal classification
Fast Nearest Neighbor Search in High-Dimensional Spaces
Heterogeneous autoregressive model with structural break using nearest neighbor truncation volatility estimators for DAX
Föderierte Nearest-Neighbor-Queries
Bias in nearest-neighbor hazard estimation
Bias in nearest-neighbor hazard estimation
On the risk of nearest neighbor rules
Nearest neighbor imputation algorithms: a critical evaluation
Quantization to speedup approximate nearest neighbor search
Kinetic Models for Topological Nearest-Neighbor Interactions
Optimized Nearest-Neighbor Classifiers Using Generated Instances
Efficient nearest neighbor search on metric time series
Weighted k-nearest-neighbor techniques and ordinal classification
Fast Nearest Neighbor Search in High-Dimensional Spaces
Heterogeneous autoregressive model with structural break using nearest neighbor truncation volatility estimators for DAX
Föderierte Nearest-Neighbor-Queries
Bias in nearest-neighbor hazard estimation
Bias in nearest-neighbor hazard estimation
On the risk of nearest neighbor rules
Nearest neighbor imputation algorithms: a critical evaluation
Quantization to speedup approximate nearest neighbor search
Kinetic Models for Topological Nearest-Neighbor Interactions
Optimized Nearest-Neighbor Classifiers Using Generated Instances
Efficient nearest neighbor search on metric time series
Weighted k-nearest-neighbor techniques and ordinal classification