Jump-robust volatility estimation using nearest neighbor truncation

Jump-robust volatility estimation using neare ...
Torben G. Andersen, Torben G. ...
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Last edited by MARC Bot
February 12, 2019 | History

Jump-robust volatility estimation using nearest neighbor truncation

"LIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">Jump-Robust Volatility Estimation using Nearest Neighbor Truncation var djConfig = { parseOnLoad: true, isDebug: false };NATIONAL BUREAU OF ECONOMIC RESEARCH HOME PAGE Jump-Robust Volatility Estimation using Nearest Neighbor TruncationUse a mirror (1020 K)Torben G. Andersen, Dobrislav Dobrev, Ernst Schaumburg NBER Working Paper No. 15533*Issued in November 2009NBER Program(s): APWe 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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Language
English

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Cover of: Jump-robust volatility estimation using nearest neighbor truncation
Jump-robust volatility estimation using nearest neighbor truncation
2009, National Bureau of Economic Research
Electronic resource in English

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Edition Notes

Title from PDF file as viewed on 12/1/2009.

Includes bibliographical references.

Also available in print.

System requirements: Adobe Acrobat Reader.

Mode of access: World Wide Web.

Published in
Cambridge, MA
Series
NBER working paper series -- working paper 15533, Working paper series (National Bureau of Economic Research : Online) -- working paper no. 2009.

Classifications

Library of Congress
HB1

The Physical Object

Format
Electronic resource

ID Numbers

Open Library
OL23969248M
LCCN
2009656087

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