EconPapers    
Economics at your fingertips  
 

Jump-robust volatility estimation using nearest neighbor truncation

Torben Andersen (), Dobrislav Dobrev and Ernst Schaumburg
Additional contact information
Dobrislav Dobrev: https://www.federalreserve.gov/econres/dobrislav-dobrev.htm

No 465, Staff Reports from Federal Reserve Bank of New York

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 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.

Keywords: Stocks - Rate of return; Stock market; Stock - Prices (search for similar items in EconPapers)
Date: 2010
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mst
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed

Downloads: (external link)
https://www.newyorkfed.org/medialibrary/media/research/staff_reports/sr465.html (text/html)
https://www.newyorkfed.org/medialibrary/media/research/staff_reports/sr465.pdf (application/pdf)

Related works:
Journal Article: Jump-robust volatility estimation using nearest neighbor truncation (2012) Downloads
Working Paper: Jump-Robust Volatility Estimation using Nearest Neighbor Truncation (2009) Downloads
Working Paper: Jump-Robust Volatility Estimation using Nearest Neighbor Truncation (2009) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:fip:fednsr:465

Ordering information: This working paper can be ordered from

Access Statistics for this paper

More papers in Staff Reports from Federal Reserve Bank of New York Contact information at EDIRC.
Bibliographic data for series maintained by Gabriella Bucciarelli ().

 
Page updated 2022-09-22
Handle: RePEc:fip:fednsr:465