Collective dynamics of stock market efficiency

Abstract Summarized by the efficient market hypothesis, the idea that stock prices fully reflect all available information is always confronted with the behavior of real-world markets. While there is plenty of evidence indicating and quantifying the efficiency of stock markets, most studies assume t...

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Autores principales:	Luiz G. A. Alves, Higor Y. D. Sigaki, Matjaž Perc, Haroldo V. Ribeiro
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/c9c2b43dc59d4acab7b93e93192deb6c
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spelling	oai:doaj.org-article:c9c2b43dc59d4acab7b93e93192deb6c2021-12-02T13:58:14ZCollective dynamics of stock market efficiency10.1038/s41598-020-78707-22045-2322https://doaj.org/article/c9c2b43dc59d4acab7b93e93192deb6c2020-12-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-78707-2https://doaj.org/toc/2045-2322Abstract Summarized by the efficient market hypothesis, the idea that stock prices fully reflect all available information is always confronted with the behavior of real-world markets. While there is plenty of evidence indicating and quantifying the efficiency of stock markets, most studies assume this efficiency to be constant over time so that its dynamical and collective aspects remain poorly understood. Here we define the time-varying efficiency of stock markets by calculating the permutation entropy within sliding time-windows of log-returns of stock market indices. We show that major world stock markets can be hierarchically classified into several groups that display similar long-term efficiency profiles. However, we also show that efficiency ranks and clusters of markets with similar trends are only stable for a few months at a time. We thus propose a network representation of stock markets that aggregates their short-term efficiency patterns into a global and coherent picture. We find this financial network to be strongly entangled while also having a modular structure that consists of two distinct groups of stock markets. Our results suggest that stock market efficiency is a collective phenomenon that can drive its operation at a high level of informational efficiency, but also places the entire system under risk of failure.Luiz G. A. AlvesHigor Y. D. SigakiMatjaž PercHaroldo V. RibeiroNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-10 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Luiz G. A. Alves Higor Y. D. Sigaki Matjaž Perc Haroldo V. Ribeiro Collective dynamics of stock market efficiency
description	Abstract Summarized by the efficient market hypothesis, the idea that stock prices fully reflect all available information is always confronted with the behavior of real-world markets. While there is plenty of evidence indicating and quantifying the efficiency of stock markets, most studies assume this efficiency to be constant over time so that its dynamical and collective aspects remain poorly understood. Here we define the time-varying efficiency of stock markets by calculating the permutation entropy within sliding time-windows of log-returns of stock market indices. We show that major world stock markets can be hierarchically classified into several groups that display similar long-term efficiency profiles. However, we also show that efficiency ranks and clusters of markets with similar trends are only stable for a few months at a time. We thus propose a network representation of stock markets that aggregates their short-term efficiency patterns into a global and coherent picture. We find this financial network to be strongly entangled while also having a modular structure that consists of two distinct groups of stock markets. Our results suggest that stock market efficiency is a collective phenomenon that can drive its operation at a high level of informational efficiency, but also places the entire system under risk of failure.
format	article
author	Luiz G. A. Alves Higor Y. D. Sigaki Matjaž Perc Haroldo V. Ribeiro
author_facet	Luiz G. A. Alves Higor Y. D. Sigaki Matjaž Perc Haroldo V. Ribeiro
author_sort	Luiz G. A. Alves
title	Collective dynamics of stock market efficiency
title_short	Collective dynamics of stock market efficiency
title_full	Collective dynamics of stock market efficiency
title_fullStr	Collective dynamics of stock market efficiency
title_full_unstemmed	Collective dynamics of stock market efficiency
title_sort	collective dynamics of stock market efficiency
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/c9c2b43dc59d4acab7b93e93192deb6c
work_keys_str_mv	AT luizgaalves collectivedynamicsofstockmarketefficiency AT higorydsigaki collectivedynamicsofstockmarketefficiency AT matjazperc collectivedynamicsofstockmarketefficiency AT haroldovribeiro collectivedynamicsofstockmarketefficiency
_version_	1718392228426022912

Collective dynamics of stock market efficiency

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