Jump-Robust Volatility Estimation using Nearest Neighbor Truncation

Torben Andersen, Dobrislav Dobrev and Ernst Schaumburg

No 15533, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We propose two new jump-robust estimators of integrated variance based on high-frequency 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 which afflict 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.

JEL-codes: C14 C15 C22 C80 G10 (search for similar items in EconPapers)
Date: 2009-11
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mst
Note: AP
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Published as Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2012. "Jump-robust volatility estimation using nearest neighbor truncation," Journal of Econometrics, Elsevier, vol. 169(1), pages 75-93.

Downloads: (external link)
http://www.nber.org/papers/w15533.pdf (application/pdf)

Related works:
Journal Article: Jump-robust volatility estimation using nearest neighbor truncation (2012)
Working Paper: Jump-robust volatility estimation using nearest neighbor truncation (2010)
Working Paper: Jump-Robust Volatility Estimation using Nearest Neighbor Truncation (2009)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nbr:nberwo:15533

Ordering information: This working paper can be ordered from
http://www.nber.org/papers/w15533

Access Statistics for this paper

More papers in NBER Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().