One-to-many matching: An alternative trading cost comparison technique

Jerry W. Liu and Donald H. Wort

Global Finance Journal, 2009, vol. 20, issue 1, 48-66

Abstract: We compare the relative merits of different matching techniques used in cross-market studies. Using the latest November 2007 data from both NASDAQ and the NYSE, we conduct simulations in which the firm characteristic distributions differ on the two matching sides. We keep the sample size small to create a difficult matching environment and highlight the relative strength of the different matching approaches. We propose a one-to-many matching method that has not been used previously in cross-market studies; each NASDAQ stock in our sample is matched with several comparable stocks from the NYSE. This method yields small matching errors than the widely used one-to-one matching process. Our simulation shows that choosing the best-matching technique actually matters. The one-to-many method consistently produces the correct result while the standard one-to-one without replacement method generates wrong answers under difficult matching environments.

Keywords: Matching; samples; One-to-many; Trading; costs (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1044-0283(09)00019-2
Full text for ScienceDirect subscribers only

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:eee:glofin:v:20:y:2009:i:1:p:48-66

Access Statistics for this article

Global Finance Journal is currently edited by Manuchehr Shahrokhi

More articles in Global Finance Journal from Elsevier
Bibliographic data for series maintained by Catherine Liu ().