The performance of bid-ask spread estimators under less than ideal conditions

Michael Bleaney and Zhiyong Li

Discussion Papers from University of Nottingham, School of Economics

Abstract: The performance of bid-ask spread estimators is investigated using simulation experiments. All estimators are much more accurate if the data are sampled at high frequency. In high-frequency data, the Huang-Stoll estimator, which requires order flow information, generally outperforms Roll-type estimators based on price information only. The exception is when there is feedback trading (order flows respond to past price movements), when the Huang-Stoll estimator is seriously biased. When only low-frequency (e.g. daily) data are available, the Corwin-Schultz estimator based on daily high and low prices is usually less inaccurate than the Huang-Stoll and Roll estimators. An important and empirically relevant exception is when the spread varies within the day; in this case the Corwin-Schultz estimator significantly overestimates the true spread. For a published version, please see Studies in Economics and Finance, Vol. 32 (2015).

Date: 2013-05
New Economics Papers: this item is included in nep-ecm and nep-mst
References: View references in EconPapers View complete reference list from CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Journal Article: The performance of bid-ask spread estimators under less than ideal conditions (2015)
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:not:notecp:13/05

Access Statistics for this paper

More papers in Discussion Papers from University of Nottingham, School of Economics School of Economics University of Nottingham University Park Nottingham NG7 2RD. Contact information at EDIRC.
Bibliographic data for series maintained by ().