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hal.structure.identifierCenter for Economic Policy Research [CEPR]
dc.contributor.authorDegryse, Hans
dc.contributor.authorDe Winne, Rudy
hal.structure.identifierDauphine Recherches en Management [DRM]
dc.contributor.authorGresse, Carole
dc.contributor.authorPayne, Richard
dc.date.accessioned2021-10-25T09:31:34Z
dc.date.available2021-10-25T09:31:34Z
dc.date.issued2021
dc.identifier.urihttps://basepub.dauphine.psl.eu/handle/123456789/22099
dc.language.isoenen
dc.subjectalgorithmic tradingen
dc.subjectfragmentationen
dc.subjectstocks tradingen
dc.subject.ddc332en
dc.subject.classificationjelG.G1.G14en
dc.subject.classificationjelG.G1.G15en
dc.subject.classificationjelG.G1.G18en
dc.titleCross-Venue Liquidity Provision: High Frequency Trading and Ghost Liquidityen
dc.typeCommunication / Conférence
dc.description.abstractenWe measure the extent to which consolidated liquidity in modern fragmented equity markets overstates true liquidity due to a phenomenon that we call Ghost Liquidity (GL). GL exists when traders place duplicate limit orders on competing venues, intending for only one of the orders to execute, and when one does execute, duplicates are cancelled. Employing data from 2013 for 91 stocks trading on their primary exchanges and three alternative platforms where order submitters are identified consistently across venues, we find that simply measured consolidated liquidity exceeds true consolidated liquidity due to the existence of GL. On average, for every 100 shares passively traded by a multi-market liquidity supplier on a given venue, around 19 shares are immediately cancelled by the same liquidity supplier on a different venue. Yet the average weight of GL in total consolidated depth, at around 4%, does not outweigh the liquidity benefits of fragmentation. GL is most pronounced for traders with a speed advantage such as high-frequency traders, in stocks exhibiting greater market fragmentation, in stocks where the tick is more likely to be binding, and on non-primary exchanges. Furthermore, GL decreases when the fraction of traders using smart order routing is large. Finally, we show that an increase in GL leads to the execution costs of slow and algo traders increasing, while those of HFTs are unaffected.en
dc.subject.ddclabelBourse, Marchés financiers. Taux d’intérêt – Stocks options – Optimisation mathématique – Analyse financièreen
dc.relation.conftitleConseil Scientifique de l'Autorité des Marchés Financiersen
dc.relation.confdate2021-04
dc.relation.confcityParisen
dc.relation.confcountryFranceen
dc.relation.forthcomingnonen
dc.description.ssrncandidatenon
dc.description.halcandidateouien
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewednonen
dc.date.updated2021-10-25T09:24:21Z
dc.subject.classificationjelHALG - Financial Economics::G1 - General Financial Markets::G14 - Information and Market Efficiency; Event Studies; Insider Tradingen
dc.subject.classificationjelHALG - Financial Economics::G1 - General Financial Markets::G15 - International Financial Marketsen
dc.subject.classificationjelHALG - Financial Economics::G1 - General Financial Markets::G18 - Government Policy and Regulationen
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