Do prices in the unmediated call auction reflect insider information? - An experimental analysis

Tobias Brünner and René Levínský ()

No 2008-090, Jena Economics Research Papers from Friedrich-Schiller-University Jena

Abstract: The unmediated call auction is a useful trading mechanism to aggregate dispersed information. Its ability to incorporate information of a single informed insider, however, is less well understood. We analyse this question by presenting a simple call auction game where both auction prices and limit prices of uninformed traders re?ect potential insider information. The predictions of the model are tested in the laboratory. While an insider improves the call auction outcomes in terms of increasing trading volume, uninformed traders fail to incorporate the (potential) insider information in their limit prices. We also derive an equilibrium relationship between auction returns and transaction costs similar to the relations that can be found in market microstructure models of continuous markets and which are commonly applied to estimate transaction costs. The experiment provides a good environment to assess the usefulness of this method to estimate transaction costs.

Keywords: call auction; asymmetric information; experiment; market microstructure (search for similar items in EconPapers)
JEL-codes: C92 D82 G14 (search for similar items in EconPapers)
Date: 2008-12-08
New Economics Papers: this item is included in nep-cta, nep-exp and nep-mst
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://oweb.b67.uni-jena.de/Papers/jerp2008/wp_2008_090.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:jrp:jrpwrp:2008-090

Access Statistics for this paper

More papers in Jena Economics Research Papers from Friedrich-Schiller-University Jena
Bibliographic data for series maintained by Markus Pasche ().