Robustness of the Separating Information Maximum Likelihood Estimation of Realized Volatility with Micro-Market Noise

Naoto Kunitomo and Seisho Sato
Additional contact information
Naoto Kunitomo: Faculty of Economics, University of Tokyo
Seisho Sato: Institute of Statistical Mathematics

No CIRJE-F-733, CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo

Abstract: For estimating the realized volatility and covariance by using high frequency data, Kunitomo and Sato (2008a,b) have proposed the Separating Information Maximum Likelihood (SIML) method when there are micro-market noises. The SIML estimator has reasonable asymptotic properties; it is consistent and it has the asymptotic normality (or the stable convergence in the general case) when the sample size is large under general conditions including non-Gaussian processes and volatility models. We also show that the SIML estimator has the asymptotic robustness in the sense that it is consistent and it has the asymptotic normality when there are autocorrelations in the market noise terms and there are endogenous correlations between the signal and noise terms.

Pages: 27pages
Date: 2010-04
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.cirje.e.u-tokyo.ac.jp/research/dp/2010/2010cf733.pdf (application/pdf)

Related works:
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:tky:fseres:2010cf733

Access Statistics for this paper

More papers in CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo Contact information at EDIRC.
Bibliographic data for series maintained by CIRJE administrative office ().