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dc.contributor.authorBeltran, Hélénaen_US
dc.contributor.authorGrammig, Joachimen_US
dc.contributor.authorMenkveld, Albert J.en_US
dc.date.accessioned2012-04-25en_US
dc.date.accessioned2012-05-02T15:45:24Z-
dc.date.available2012-05-02T15:45:24Z-
dc.date.issued2005en_US
dc.identifier.urihttp://hdl.handle.net/10419/57744-
dc.description.abstractElectronic limit order books are ubiquitous in markets today. However, theoretical models for limit order markets fail to explain the real world data well. Sandas (2001) tests the classic Glosten (1994) model for order book equilibrium and rejects it. We reconfirm this result for one of the largest European stock markets. We then relax one of the model's assumptions and allow the informational content of trades to change over time. Adapting Hasbrouck's (1991a,b) methodology to estimate time varying trade informativeness we find that it is a slowly mean reverting process. By conditioning on trade informativeness, we find support for the Glosten model's implication that books are more shallow during times of informative market orders. However, a high level of liquidity supply is committed up to an economically significant trade size volume, even when trade informativeness is high. This can be seen as a vindication of the open order book design which dispenses with dedicated market makers. We also find evidence for a market order trader population which is quite heterogenous with respect to price sensitivity.en_US
dc.language.isoengen_US
dc.publisherCentre for Financial Research Cologneen_US
dc.relation.ispartofseriesCFR Working Paper 05-05en_US
dc.subject.jelG10en_US
dc.subject.ddc330en_US
dc.subject.keywordInformational content of tradesen_US
dc.subject.keywordlimit order booken_US
dc.titleUnderstanding the limit order book: Conditioning on trade informativenessen_US
dc.typeWorking Paperen_US
dc.identifier.ppn699911494en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
dc.identifier.repecRePEc:zbw:cfrwps:0505-
Appears in Collections:CFR Working Papers, Centre for Financial Research (CFR), Universität Köln

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