|
EconStor >
Federal Reserve Bank of New York >
Staff Reports, Federal Reserve Bank of New York >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10419/60837
|
| | |
| Title: | | Jump-robust volatility estimation using nearest neighbor truncation  |
| 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
|
| |
| | |
Download bibliographical data as:
BibTeX
|
| |
Share on:http://hdl.handle.net/10419/60837
|
Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.
|