dc.creatorZhou, Hao
dc.creatorKalev, Petko S.
dc.creatorFrino, Alex
dc.date.accessioned2020-08-24T14:47:14Z
dc.date.accessioned2022-09-23T18:46:21Z
dc.date.available2020-08-24T14:47:14Z
dc.date.available2022-09-23T18:46:21Z
dc.date.created2020-08-24T14:47:14Z
dc.identifierhttps://doi.org/10.1016/j.pacfin.2020.101358
dc.identifierhttp://hdl.handle.net/20.500.12010/12136
dc.identifierhttps://doi.org/10.1016/j.pacfin.2020.101358
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3507116
dc.description.abstractDoes Algorithmic Trading (AT) exacerbate price swings in turbulent markets? We find that stocks with high AT experience less price drops (surges) on days when the market declines (increases) for more than 2%. This result is consistent with the view that AT minimizes price pressures and mitigates transitory pricing errors. Further analyses show that the net imbalances of AT liquidity demand and supply orders have smaller price impacts compared to non-AT net order imbalances and algorithmic traders reduce their price pressure by executing their trades based on the prevailing volume-weighted average prices.
dc.languageeng
dc.publisherPacific-Basin Finance Journal
dc.rightsinfo:eu-repo/semantics/embargoedAccess
dc.rightsAcceso restringido
dc.sourcereponame:Expeditio Repositorio Institucional UJTL
dc.sourceinstname:Universidad de Bogotá Jorge Tadeo Lozano
dc.subjectAlgorithmic trading
dc.subjectOrder imbalance
dc.subjectTurbulent markets
dc.subjectVolume-weighted average price
dc.subjectPrice swing
dc.titleAlgorithmic trading in turbulent markets


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