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Jump-robust volatility estimation using nearest neighbor truncation

Author: Torben G Andersen; Dobrislav Dobrev; Ernst Schaumburg; National Bureau of Economic Research.
Publisher: Cambridge, MA : National Bureau of Economic Research, c 2009.
Series: Working paper series (National Bureau of Economic Research : Online), working paper no. 15533.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
"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  Read more...
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Details

Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Torben G Andersen; Dobrislav Dobrev; Ernst Schaumburg; National Bureau of Economic Research.
OCLC Number: 467933140
Notes: Title from PDF file as viewed on 12/1/2009.
Description: 1 online resource (35 pages) : illustrations, digital.
Series Title: Working paper series (National Bureau of Economic Research : Online), working paper no. 15533.
Responsibility: Torben G. Andersen, Dobrislav Dobrev, Ernst Schaumburg.

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"--National Bureau of Economic Research web site.

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