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Jump-robust volatility estimation using nearest neighbor truncation

Torben Andersen (), Dobrislav Dobrev and Ernst Schaumburg

Journal of Econometrics, 2012, vol. 169, issue 1, 75-93

Abstract: We propose two new jump-robust estimators of integrated variance that allow for an asymptotic limit theory in the presence of jumps. Specifically, our MedRV estimator has better efficiency properties than the tripower variation measure and displays better finite-sample robustness to jumps and small (“zero”) returns. We stress the benefits of local volatility measures using short return blocks, as this greatly alleviates the downward biases stemming from rapid fluctuations in volatility, including diurnal (intraday) U-shape patterns. An empirical investigation of the Dow Jones 30 stocks and extensive simulations corroborate the robustness and efficiency properties of our nearest neighbor truncation estimators.

Keywords: High-frequency data; Integrated variance; Finite activity jumps; Realized volatility; Jump robustness; Nearest neighbor truncation; Intraday U-shape patterns (search for similar items in EconPapers)
JEL-codes: C14 C15 C22 C80 G10 (search for similar items in EconPapers)
Date: 2012
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Related works:
Working Paper: Jump-robust volatility estimation using nearest neighbor truncation (2010) Downloads
Working Paper: Jump-Robust Volatility Estimation using Nearest Neighbor Truncation (2009) Downloads
Working Paper: Jump-Robust Volatility Estimation using Nearest Neighbor Truncation (2009) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:169:y:2012:i:1:p:75-93

DOI: 10.1016/j.jeconom.2012.01.011

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Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

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