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The adaptive market hypothesis and high frequency trading

This paper uses NASDAQ order book data for the S&P 500 exchange traded fund (SPY) to examine the relationship between one-minute, informational market efficiency and high frequency trading (HFT). We find that the level of efficiency varies widely over time and appears to cluster. Periods of high...

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Detalles Bibliográficos
Autores principales: Meng, Ke, Li, Shouhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8682897/
https://www.ncbi.nlm.nih.gov/pubmed/34919550
http://dx.doi.org/10.1371/journal.pone.0260724
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author Meng, Ke
Li, Shouhao
author_facet Meng, Ke
Li, Shouhao
author_sort Meng, Ke
collection PubMed
description This paper uses NASDAQ order book data for the S&P 500 exchange traded fund (SPY) to examine the relationship between one-minute, informational market efficiency and high frequency trading (HFT). We find that the level of efficiency varies widely over time and appears to cluster. Periods of high efficiency are followed by periods of low efficiency and vice versa. Further, we find that HFT activity is higher during periods of low efficiency. This supports the argument that HFTs seek profits and risk reduction by actively processing information, through limit order additions and cancellations, during periods of lower efficiency and revert to more passive market-making and rebate-generation during periods of higher efficiency. These findings support the argument that the adaptive market hypothesis (AMH) is an appropriate description of how prices evolve to incorporate information.
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spelling pubmed-86828972021-12-18 The adaptive market hypothesis and high frequency trading Meng, Ke Li, Shouhao PLoS One Research Article This paper uses NASDAQ order book data for the S&P 500 exchange traded fund (SPY) to examine the relationship between one-minute, informational market efficiency and high frequency trading (HFT). We find that the level of efficiency varies widely over time and appears to cluster. Periods of high efficiency are followed by periods of low efficiency and vice versa. Further, we find that HFT activity is higher during periods of low efficiency. This supports the argument that HFTs seek profits and risk reduction by actively processing information, through limit order additions and cancellations, during periods of lower efficiency and revert to more passive market-making and rebate-generation during periods of higher efficiency. These findings support the argument that the adaptive market hypothesis (AMH) is an appropriate description of how prices evolve to incorporate information. Public Library of Science 2021-12-17 /pmc/articles/PMC8682897/ /pubmed/34919550 http://dx.doi.org/10.1371/journal.pone.0260724 Text en © 2021 Meng, Li https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Meng, Ke
Li, Shouhao
The adaptive market hypothesis and high frequency trading
title The adaptive market hypothesis and high frequency trading
title_full The adaptive market hypothesis and high frequency trading
title_fullStr The adaptive market hypothesis and high frequency trading
title_full_unstemmed The adaptive market hypothesis and high frequency trading
title_short The adaptive market hypothesis and high frequency trading
title_sort adaptive market hypothesis and high frequency trading
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8682897/
https://www.ncbi.nlm.nih.gov/pubmed/34919550
http://dx.doi.org/10.1371/journal.pone.0260724
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