MARC Record from Library of Congress

LEADER: 02302cam a22003017a 4500
001 2009656087
003 DLC
005 20091230084601.0
007 cr |||||||||||
008 091201s2009 mau sb 000 0 eng
010 $a 2009656087
040 $aDLC$cDLC
050 00 $aHB1
100 1 $aAndersen, Torben G.$q(Torben Gustav)
245 10 $aJump-robust volatility estimation using nearest neighbor truncation$h[electronic resource] /$cTorben G. Andersen, Dobrislav Dobrev, Ernst Schaumburg.
260 $aCambridge, MA :$bNational Bureau of Economic Research,$cc 2009.
490 1 $aNBER working paper series ;$vworking paper 15533
538 $aSystem requirements: Adobe Acrobat Reader.
538 $aMode of access: World Wide Web.
500 $aTitle from PDF file as viewed on 12/1/2009.
530 $aAlso available in print.
504 $aIncludes bibliographical references.
520 3 $a"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.
700 1 $aDobrev, Dobrislav.
700 1 $aSchaumburg, Ernst.
710 2 $aNational Bureau of Economic Research.
830 0 $aWorking paper series (National Bureau of Economic Research : Online) ;$vworking paper no. 15533.
856 40 $uhttp://www.nber.org/papers/w15533