Fractional dynamics in financial indexes

Bibliographic Details
Main Author: Machado, J. A. Tenreiro
Publication Date: 2012
Other Authors: Duarte, Fernando B., Duarte, Gonçalo Monteiro
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.22/4134
Summary: The goal of this study is the analysis of the dynamical properties of financial data series from 32 worldwide stock market indices during the period 2000–2009 at a daily time horizon. Stock market indices are examples of complex interacting systems for which a huge amount of data exists. The methods and algorithms that have been explored for the description of physical phenomena become an effective background in the analysis of economical data. In this perspective are applied the classical concepts of signal analysis, Fourier transform and methods of fractional calculus. The results reveal classification patterns typical of fractional dynamical systems.
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spelling Fractional dynamics in financial indexesFourier transformPower lawDynamicsFractional calculusThe goal of this study is the analysis of the dynamical properties of financial data series from 32 worldwide stock market indices during the period 2000–2009 at a daily time horizon. Stock market indices are examples of complex interacting systems for which a huge amount of data exists. The methods and algorithms that have been explored for the description of physical phenomena become an effective background in the analysis of economical data. In this perspective are applied the classical concepts of signal analysis, Fourier transform and methods of fractional calculus. The results reveal classification patterns typical of fractional dynamical systems.World ScientificREPOSITÓRIO P.PORTOMachado, J. A. TenreiroDuarte, Fernando B.Duarte, Gonçalo Monteiro2014-03-06T14:47:26Z20122012-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/4134eng0218-12741793-655110.1142/S0218127412502495info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-04-02T03:09:44Zoai:recipp.ipp.pt:10400.22/4134Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T00:44:45.943091Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Fractional dynamics in financial indexes
title Fractional dynamics in financial indexes
spellingShingle Fractional dynamics in financial indexes
Machado, J. A. Tenreiro
Fourier transform
Power law
Dynamics
Fractional calculus
title_short Fractional dynamics in financial indexes
title_full Fractional dynamics in financial indexes
title_fullStr Fractional dynamics in financial indexes
title_full_unstemmed Fractional dynamics in financial indexes
title_sort Fractional dynamics in financial indexes
author Machado, J. A. Tenreiro
author_facet Machado, J. A. Tenreiro
Duarte, Fernando B.
Duarte, Gonçalo Monteiro
author_role author
author2 Duarte, Fernando B.
Duarte, Gonçalo Monteiro
author2_role author
author
dc.contributor.none.fl_str_mv REPOSITÓRIO P.PORTO
dc.contributor.author.fl_str_mv Machado, J. A. Tenreiro
Duarte, Fernando B.
Duarte, Gonçalo Monteiro
dc.subject.por.fl_str_mv Fourier transform
Power law
Dynamics
Fractional calculus
topic Fourier transform
Power law
Dynamics
Fractional calculus
description The goal of this study is the analysis of the dynamical properties of financial data series from 32 worldwide stock market indices during the period 2000–2009 at a daily time horizon. Stock market indices are examples of complex interacting systems for which a huge amount of data exists. The methods and algorithms that have been explored for the description of physical phenomena become an effective background in the analysis of economical data. In this perspective are applied the classical concepts of signal analysis, Fourier transform and methods of fractional calculus. The results reveal classification patterns typical of fractional dynamical systems.
publishDate 2012
dc.date.none.fl_str_mv 2012
2012-01-01T00:00:00Z
2014-03-06T14:47:26Z
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url http://hdl.handle.net/10400.22/4134
dc.language.iso.fl_str_mv eng
language eng
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1793-6551
10.1142/S0218127412502495
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dc.publisher.none.fl_str_mv World Scientific
publisher.none.fl_str_mv World Scientific
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