Jump-Robust Volatility Estimation Using Nearest Neighbor Truncation
Torben G. Andersen
Northwestern University - Kellogg School of Management; National Bureau of Economic Research (NBER); University of Aarhus - CREATES
Federal Reserve Board
Federal Reserve Banks - Federal Reserve Bank of New York
August 1, 2010
FRB of New York Staff Report No. 465
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 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.
Number of Pages in PDF File: 37
Keywords: Integrated Volatility, Jump Robust
JEL Classification: C14, C15, C22, C80, G10working papers series
Date posted: August 5, 2010
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