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Algorithmic trading in turbulent markets()

Does 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 tra...

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Detalles Bibliográficos
Autores principales: Zhou, Hao, Kalev, Petko S., Frino, Alex
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7276139/
http://dx.doi.org/10.1016/j.pacfin.2020.101358
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author Zhou, Hao
Kalev, Petko S.
Frino, Alex
author_facet Zhou, Hao
Kalev, Petko S.
Frino, Alex
author_sort Zhou, Hao
collection PubMed
description Does 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.
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spelling pubmed-72761392020-06-08 Algorithmic trading in turbulent markets() Zhou, Hao Kalev, Petko S. Frino, Alex Pacific-Basin Finance Journal Article Does 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. Elsevier B.V. 2020-09 2020-06-07 /pmc/articles/PMC7276139/ http://dx.doi.org/10.1016/j.pacfin.2020.101358 Text en © 2020 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Zhou, Hao
Kalev, Petko S.
Frino, Alex
Algorithmic trading in turbulent markets()
title Algorithmic trading in turbulent markets()
title_full Algorithmic trading in turbulent markets()
title_fullStr Algorithmic trading in turbulent markets()
title_full_unstemmed Algorithmic trading in turbulent markets()
title_short Algorithmic trading in turbulent markets()
title_sort algorithmic trading in turbulent markets()
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7276139/
http://dx.doi.org/10.1016/j.pacfin.2020.101358
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AT frinoalex algorithmictradinginturbulentmarkets