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A behavioral approach to instability pathways in financial markets

We introduce an indicator that aims to detect the emergence of market instabilities by quantifying the intensity of self-organizing processes arising from stock returns’ co-movements. In financial markets, phenomena like imitation, herding and positive feedbacks characterize the emergence of endogen...

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Autores principales: Spelta, Alessandro, Flori, Andrea, Pecora, Nicolò, Buldyrev, Sergey, Pammolli, Fabio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7136275/
https://www.ncbi.nlm.nih.gov/pubmed/32249781
http://dx.doi.org/10.1038/s41467-020-15356-z
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author Spelta, Alessandro
Flori, Andrea
Pecora, Nicolò
Buldyrev, Sergey
Pammolli, Fabio
author_facet Spelta, Alessandro
Flori, Andrea
Pecora, Nicolò
Buldyrev, Sergey
Pammolli, Fabio
author_sort Spelta, Alessandro
collection PubMed
description We introduce an indicator that aims to detect the emergence of market instabilities by quantifying the intensity of self-organizing processes arising from stock returns’ co-movements. In financial markets, phenomena like imitation, herding and positive feedbacks characterize the emergence of endogenous instabilities, which can modify the qualitative and quantitative behavior of the underlying system. The impossibility to formalize ex-ante the dynamic laws that rule the evolution of financial systems motivates the use of a parsimonious synthetic indicator to detect the disruption of an existing equilibrium configuration. Here we show that the emergence of an interconnected sub-graph of stock returns co-movements from a broader market index is a signal of an out-of-equilibrium transition of the underlying system. To test the validity of our approach, we propose a model-free application that builds on the identification of up and down market phases.
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spelling pubmed-71362752020-04-08 A behavioral approach to instability pathways in financial markets Spelta, Alessandro Flori, Andrea Pecora, Nicolò Buldyrev, Sergey Pammolli, Fabio Nat Commun Article We introduce an indicator that aims to detect the emergence of market instabilities by quantifying the intensity of self-organizing processes arising from stock returns’ co-movements. In financial markets, phenomena like imitation, herding and positive feedbacks characterize the emergence of endogenous instabilities, which can modify the qualitative and quantitative behavior of the underlying system. The impossibility to formalize ex-ante the dynamic laws that rule the evolution of financial systems motivates the use of a parsimonious synthetic indicator to detect the disruption of an existing equilibrium configuration. Here we show that the emergence of an interconnected sub-graph of stock returns co-movements from a broader market index is a signal of an out-of-equilibrium transition of the underlying system. To test the validity of our approach, we propose a model-free application that builds on the identification of up and down market phases. Nature Publishing Group UK 2020-04-06 /pmc/articles/PMC7136275/ /pubmed/32249781 http://dx.doi.org/10.1038/s41467-020-15356-z Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Spelta, Alessandro
Flori, Andrea
Pecora, Nicolò
Buldyrev, Sergey
Pammolli, Fabio
A behavioral approach to instability pathways in financial markets
title A behavioral approach to instability pathways in financial markets
title_full A behavioral approach to instability pathways in financial markets
title_fullStr A behavioral approach to instability pathways in financial markets
title_full_unstemmed A behavioral approach to instability pathways in financial markets
title_short A behavioral approach to instability pathways in financial markets
title_sort behavioral approach to instability pathways in financial markets
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7136275/
https://www.ncbi.nlm.nih.gov/pubmed/32249781
http://dx.doi.org/10.1038/s41467-020-15356-z
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