TY  - JOUR
AU  - Andersen,Torben G.
AU  - Dobrev,Dobrislav
AU  - Schaumburg,Ernst
TI  - Jump-Robust Volatility Estimation using Nearest Neighbor Truncation
JF  - National Bureau of Economic Research Working Paper Series
VL  - No. 15533
PY  - 2009
Y2  - November 2009
UR  - http://www.nber.org/papers/w15533
L1  - http://www.nber.org/papers/w15533.pdf
N1  - Author contact info:
Torben G. Andersen
Kellogg School of Management
Northwestern University
2001 Sheridan Road
Evanston, IL  60208
Tel: 847/467-1285
Fax: 847/491-5719
E-Mail: t-andersen@kellogg.northwestern.edu

Dobrislav Dobrev
Federal Reserve Board of Governors
20th Street and Constitution Avenue NW
Washington, DC 20551
E-Mail: Dobrislav.P.Dobrev@frb.gov

Ernst Schaumburg
Federal Reserve Bank of New York
33 Liberty Street
New York, NY 10045
E-Mail: ernst.schaumburg@ny.frb.org
AB  - 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.
ER  -