On equity market inefficiency during the COVID-19 pandemic

We show that during the weeks following the initiation of the COVID-19 pandemic, the United States equity market was inefficient. This is demonstrated by showing that utility maximizing agents over the time period ranging from mid-February to late March 2020 can generate statistically significant pr...

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Detalles Bibliográficos
Autores principales: Navratil, Robert, Taylor, Stephen, Vecer, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9759836/
https://www.ncbi.nlm.nih.gov/pubmed/36570865
http://dx.doi.org/10.1016/j.irfa.2021.101820
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author Navratil, Robert
Taylor, Stephen
Vecer, Jan
author_facet Navratil, Robert
Taylor, Stephen
Vecer, Jan
author_sort Navratil, Robert
collection PubMed
description We show that during the weeks following the initiation of the COVID-19 pandemic, the United States equity market was inefficient. This is demonstrated by showing that utility maximizing agents over the time period ranging from mid-February to late March 2020 can generate statistically significant profits by utilizing only historical price and virus related data to forecast future equity ETF returns. We generalize Merton’s optimal portfolio problem using a novel method based upon a likelihood ratio in order to construct a dynamic trading strategy for utility maximizing agents. These strategies are shown to have statistically significant profitability and strong risk and performance statistics during the COVID-19 time-frame.
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spelling pubmed-97598362022-12-19 On equity market inefficiency during the COVID-19 pandemic Navratil, Robert Taylor, Stephen Vecer, Jan Int Rev Financ Anal Article We show that during the weeks following the initiation of the COVID-19 pandemic, the United States equity market was inefficient. This is demonstrated by showing that utility maximizing agents over the time period ranging from mid-February to late March 2020 can generate statistically significant profits by utilizing only historical price and virus related data to forecast future equity ETF returns. We generalize Merton’s optimal portfolio problem using a novel method based upon a likelihood ratio in order to construct a dynamic trading strategy for utility maximizing agents. These strategies are shown to have statistically significant profitability and strong risk and performance statistics during the COVID-19 time-frame. Elsevier Inc. 2021-10 2021-07-02 /pmc/articles/PMC9759836/ /pubmed/36570865 http://dx.doi.org/10.1016/j.irfa.2021.101820 Text en © 2021 Elsevier Inc. 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
Navratil, Robert
Taylor, Stephen
Vecer, Jan
On equity market inefficiency during the COVID-19 pandemic
title On equity market inefficiency during the COVID-19 pandemic
title_full On equity market inefficiency during the COVID-19 pandemic
title_fullStr On equity market inefficiency during the COVID-19 pandemic
title_full_unstemmed On equity market inefficiency during the COVID-19 pandemic
title_short On equity market inefficiency during the COVID-19 pandemic
title_sort on equity market inefficiency during the covid-19 pandemic
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9759836/
https://www.ncbi.nlm.nih.gov/pubmed/36570865
http://dx.doi.org/10.1016/j.irfa.2021.101820
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