Statistical arbitrage: an approach from econophysics

The statistical arbitrage strategy emerged in the mid-80s, developed by a group of scientists associated with Morgan Stanley's investment bank. This approach entails the choice of a pair of financial assets that have traditionally shown parallel movements. A profit can be achieved by establ...

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Detalles Bibliográficos
Autores: Ramos-Requena, José Pedro, García Amate, Antonio Jesús, López-García, María de las Nieves
Tipo de recurso: capítulo de libro
Estado:Versión aceptada para publicación
Fecha de publicación:2025
País:España
Institución:Universidad Pública de Navarra
Repositorio:Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
OAI Identifier:oai:academica-e.unavarra.es:2454/55690
Acceso en línea:https://hdl.handle.net/2454/55690
Access Level:acceso embargado
Palabra clave:Statistical arbitrage
Pairs trading
Econophysics
Hurst exponent
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spelling Statistical arbitrage: an approach from econophysicsRamos-Requena, José PedroGarcía Amate, Antonio JesúsLópez-García, María de las NievesStatistical arbitragePairs tradingEconophysicsHurst exponentThe statistical arbitrage strategy emerged in the mid-80s, developed by a group of scientists associated with Morgan Stanley's investment bank. This approach entails the choice of a pair of financial assets that have traditionally shown parallel movements. A profit can be achieved by establishing a long-short position on this pair when they move apart, resulting in gains upon their subsequent return to an average when closing the position. In this chapter, we are going to conduct a study on the application of this methodology by applying methods from the field of econophysics. To do this, we will examine the Hurst exponent method, which is one of the approaches that best fits to measure the mean reversion of financial series.SpringerGestión de EmpresasEnpresen Kudeaketa2025info:eu-repo/semantics/bookPartinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttps://hdl.handle.net/2454/55690reponame:Academica-e. Repositorio Institucional de la Universidad Pública de Navarrainstname:Universidad Pública de NavarraInglés© 2025 The Author(s), under exclusive license to Springer Nature Switzerland AG.info:eu-repo/semantics/embargoedAccessoai:academica-e.unavarra.es:2454/556902026-06-17T12:41:47Z
dc.title.none.fl_str_mv Statistical arbitrage: an approach from econophysics
title Statistical arbitrage: an approach from econophysics
spellingShingle Statistical arbitrage: an approach from econophysics
Ramos-Requena, José Pedro
Statistical arbitrage
Pairs trading
Econophysics
Hurst exponent
title_short Statistical arbitrage: an approach from econophysics
title_full Statistical arbitrage: an approach from econophysics
title_fullStr Statistical arbitrage: an approach from econophysics
title_full_unstemmed Statistical arbitrage: an approach from econophysics
title_sort Statistical arbitrage: an approach from econophysics
dc.creator.none.fl_str_mv Ramos-Requena, José Pedro
García Amate, Antonio Jesús
López-García, María de las Nieves
author Ramos-Requena, José Pedro
author_facet Ramos-Requena, José Pedro
García Amate, Antonio Jesús
López-García, María de las Nieves
author_role author
author2 García Amate, Antonio Jesús
López-García, María de las Nieves
author2_role author
author
dc.contributor.none.fl_str_mv Gestión de Empresas
Enpresen Kudeaketa
dc.subject.none.fl_str_mv Statistical arbitrage
Pairs trading
Econophysics
Hurst exponent
topic Statistical arbitrage
Pairs trading
Econophysics
Hurst exponent
description The statistical arbitrage strategy emerged in the mid-80s, developed by a group of scientists associated with Morgan Stanley's investment bank. This approach entails the choice of a pair of financial assets that have traditionally shown parallel movements. A profit can be achieved by establishing a long-short position on this pair when they move apart, resulting in gains upon their subsequent return to an average when closing the position. In this chapter, we are going to conduct a study on the application of this methodology by applying methods from the field of econophysics. To do this, we will examine the Hurst exponent method, which is one of the approaches that best fits to measure the mean reversion of financial series.
publishDate 2025
dc.date.none.fl_str_mv 2025
dc.type.none.fl_str_mv info:eu-repo/semantics/bookPart
info:eu-repo/semantics/acceptedVersion
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status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2454/55690
url https://hdl.handle.net/2454/55690
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv © 2025 The Author(s), under exclusive license to Springer Nature Switzerland AG.
info:eu-repo/semantics/embargoedAccess
rights_invalid_str_mv © 2025 The Author(s), under exclusive license to Springer Nature Switzerland AG.
eu_rights_str_mv embargoedAccess
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dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
instname:Universidad Pública de Navarra
instname_str Universidad Pública de Navarra
reponame_str Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
collection Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
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repository.mail.fl_str_mv
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