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Title:Jump-robust volatility estimation using nearest neighbor truncation PDF Logo
Authors:Andersen, Torben G.
Dobrev, Dobrislav
Schaumburg, Ernst
Issue Date:2010
Series/Report no.:Staff Report, Federal Reserve Bank of New York 465
Abstract: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.
Subjects:Integrated volatility
jump robust
JEL:C14
C15
C22
C80
G10
Document Type:Working Paper
Appears in Collections:Staff Reports, Federal Reserve Bank of New York

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