Bipower-type estimation in a noisy diffusion setting
| dc.contributor.author | Podolskij, Mark | |
| dc.contributor.author | Vetter, Mathias | |
| dc.date.accessioned | 2009-01-13T08:02:17Z | |
| dc.date.available | 2009-01-13T08:02:17Z | |
| dc.date.issued | 2009-01-13T08:02:17Z | |
| dc.description.abstract | We consider a new class of estimators for volatility functionals in the setting of frequently observed Ito diffusions which are disturbed by i.i.d. noise. These statistics extend the approach of pre-averaging as a general method for the estimation of the integrated volatility in the presence of microstructure noise and are closely related to the original concept of bipower variation in the no-noise case. We show that this approach provides efficient estimators for a large class of integrated powers of volatility and prove the associated (stable) central limit theorems. In a more general Ito semimartingale framework this method can be used to define both estimators for the entire quadratic variation of the underlying process and jump-robust estimators which are consistent for various functionals of volatility. As a by-product we obtain a simple test for the presence of jumps in the underlying semimartingale. | en |
| dc.identifier.uri | http://hdl.handle.net/2003/25990 | |
| dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-14128 | |
| dc.language.iso | en | de |
| dc.subject | Bipower variation | en |
| dc.subject | Central limit theorem | en |
| dc.subject | High-frequency data | en |
| dc.subject | Microstructure noise | en |
| dc.subject | Quadratic variation | en |
| dc.subject | Semimartingale theory | en |
| dc.subject | Test for jumps | en |
| dc.subject.ddc | 004 | |
| dc.title | Bipower-type estimation in a noisy diffusion setting | en |
| dc.type | Text | de |
| dc.type.publicationtype | report | en |
| dcterms.accessRights | open access |