Designing realized kernels to measure the ex post variation of equity prices in the presence of noise

Publication: Research - peer-reviewJournal article

  • Department of Mathematical Sciences
  • School of Economics and Management
This paper shows how to use realized kernels to carry out efficient feasible inference on the ex post variation of underlying equity prices in the presence of simple models of market frictions. The weights can be chosen to achieve the best possible rate of convergence and to have an asymptotic variance which equals that of the maximum likelihood estimator in the parametric version of this problem. Realized kernels can also be selected to (i) be analyzed using endogenously spaced data such as that in data bases on transactions, (ii) allow for market frictions which are endogenous, and (iii) allow for temporally dependent noise. The finite sample performance of our estimators is studied using simulation, while empirical work illustrates their use in practice.
Original languageEnglish
JournalEconometrica
Volume76
Issue number6
Pages (from-to)1481-1536
Number of pages56
ISSN0012-9682
DOIs
StatePublished - 2008

See relations at Aarhus University Citationformats

ID: 10611956