Publication Type

Journal Article

Version

acceptedVersion

Publication Date

1-2017

Abstract

We study the market microstructure noise-variance estimation of high-frequency stock prices. Based on the Hansen and Lunde (2006) approach, we propose estimates using subsampling method at different time scales. We conduct a Monte Carlo study to compare our method against others in the literature. Our results show that our proposed estimates have lower (absolute) mean error and root mean-squared error, and their performance is quite stable at different time scales.

Keywords

High-frequency data, Microstructure noise, Noise-to-signal ratio, Realized variance

Discipline

Econometrics | Economic Theory

Research Areas

Econometrics

Publication

Economics Letters

Volume

150

First Page

59

Last Page

62

ISSN

0165-1765

Identifier

10.1016/j.econlet.2016.11.009

Publisher

Elsevier

Additional URL

https://doi.org/10.1016/j.econlet.2016.11.009

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