An entropy based in wavelet leaders to quantify the local regularity of a signal and its application to analyze the Dow Jones index

Autores
Rosenblatt, Mariel; Serrano, Eduardo Pedro; Figliola, Maria Alejandra
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Local regularity analysis is useful in many fields, such as financial analysis, fluid mechanics,PDE theory, signal and image processing. Different quantifiers have been proposedto measure the local regularity of a function. In this paper we present a new quantifier of local regularity of a signal: the pointwise wavelet leaders entropy. We define this new measure of regularity by combining the concept of entropy, coming from the information theory and statistical mechanics, with the wavelet leaders coefficients. Also we establish its inverse relation with one of the well-known regularity exponents, the pointwise H¨older exponent. Finally, we apply this methodology to the financial data series of the Dow Jones Industrial Average Index, registered in the period 1928?2011, in order to compare the temporal evolution of the pointwise H¨older exponent and the pointwise wavelet leaders entropy. The analysis reveals that temporal variation of these quantifiers reflects the evolution of the Dow Jones Industrial Average Index and identifies historical crisis events.
Fil: Rosenblatt, Mariel. Universidad Nacional de General Sarmiento. Instituto del Desarrollo Humano; Argentina
Fil: Serrano, Eduardo Pedro. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina
Fil: Figliola, Maria Alejandra. Universidad Nacional de General Sarmiento. Instituto del Desarrollo Humano; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
LOCAL REGULARITY
ENTROPY
WAVELET LEADERS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/243822
Acceder
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network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling An entropy based in wavelet leaders to quantify the local regularity of a signal and its application to analyze the Dow Jones indexRosenblatt, MarielSerrano, Eduardo PedroFigliola, Maria AlejandraLOCAL REGULARITYENTROPYWAVELET LEADERShttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1Local regularity analysis is useful in many fields, such as financial analysis, fluid mechanics,PDE theory, signal and image processing. Different quantifiers have been proposedto measure the local regularity of a function. In this paper we present a new quantifier of local regularity of a signal: the pointwise wavelet leaders entropy. We define this new measure of regularity by combining the concept of entropy, coming from the information theory and statistical mechanics, with the wavelet leaders coefficients. Also we establish its inverse relation with one of the well-known regularity exponents, the pointwise H¨older exponent. Finally, we apply this methodology to the financial data series of the Dow Jones Industrial Average Index, registered in the period 1928?2011, in order to compare the temporal evolution of the pointwise H¨older exponent and the pointwise wavelet leaders entropy. The analysis reveals that temporal variation of these quantifiers reflects the evolution of the Dow Jones Industrial Average Index and identifies historical crisis events.Fil: Rosenblatt, Mariel. Universidad Nacional de General Sarmiento. Instituto del Desarrollo Humano; ArgentinaFil: Serrano, Eduardo Pedro. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; ArgentinaFil: Figliola, Maria Alejandra. Universidad Nacional de General Sarmiento. Instituto del Desarrollo Humano; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaWorld Scientific2012-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/243822Rosenblatt, Mariel; Serrano, Eduardo Pedro; Figliola, Maria Alejandra; An entropy based in wavelet leaders to quantify the local regularity of a signal and its application to analyze the Dow Jones index; World Scientific; International Journal of Wavelets, Multiresolution and Information Processing; 10; 5; 10-2012; 1-170219-6913CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1142/S0219691312500488info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:14:11Zoai:ri.conicet.gov.ar:11336/243822instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:14:11.702CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv An entropy based in wavelet leaders to quantify the local regularity of a signal and its application to analyze the Dow Jones index
title An entropy based in wavelet leaders to quantify the local regularity of a signal and its application to analyze the Dow Jones index
spellingShingle An entropy based in wavelet leaders to quantify the local regularity of a signal and its application to analyze the Dow Jones index
Rosenblatt, Mariel
LOCAL REGULARITY
ENTROPY
WAVELET LEADERS
title_short An entropy based in wavelet leaders to quantify the local regularity of a signal and its application to analyze the Dow Jones index
title_full An entropy based in wavelet leaders to quantify the local regularity of a signal and its application to analyze the Dow Jones index
title_fullStr An entropy based in wavelet leaders to quantify the local regularity of a signal and its application to analyze the Dow Jones index
title_full_unstemmed An entropy based in wavelet leaders to quantify the local regularity of a signal and its application to analyze the Dow Jones index
title_sort An entropy based in wavelet leaders to quantify the local regularity of a signal and its application to analyze the Dow Jones index
dc.creator.none.fl_str_mv Rosenblatt, Mariel
Serrano, Eduardo Pedro
Figliola, Maria Alejandra
author Rosenblatt, Mariel
author_facet Rosenblatt, Mariel
Serrano, Eduardo Pedro
Figliola, Maria Alejandra
author_role author
author2 Serrano, Eduardo Pedro
Figliola, Maria Alejandra
author2_role author
author
dc.subject.none.fl_str_mv LOCAL REGULARITY
ENTROPY
WAVELET LEADERS
topic LOCAL REGULARITY
ENTROPY
WAVELET LEADERS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Local regularity analysis is useful in many fields, such as financial analysis, fluid mechanics,PDE theory, signal and image processing. Different quantifiers have been proposedto measure the local regularity of a function. In this paper we present a new quantifier of local regularity of a signal: the pointwise wavelet leaders entropy. We define this new measure of regularity by combining the concept of entropy, coming from the information theory and statistical mechanics, with the wavelet leaders coefficients. Also we establish its inverse relation with one of the well-known regularity exponents, the pointwise H¨older exponent. Finally, we apply this methodology to the financial data series of the Dow Jones Industrial Average Index, registered in the period 1928?2011, in order to compare the temporal evolution of the pointwise H¨older exponent and the pointwise wavelet leaders entropy. The analysis reveals that temporal variation of these quantifiers reflects the evolution of the Dow Jones Industrial Average Index and identifies historical crisis events.
Fil: Rosenblatt, Mariel. Universidad Nacional de General Sarmiento. Instituto del Desarrollo Humano; Argentina
Fil: Serrano, Eduardo Pedro. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina
Fil: Figliola, Maria Alejandra. Universidad Nacional de General Sarmiento. Instituto del Desarrollo Humano; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description Local regularity analysis is useful in many fields, such as financial analysis, fluid mechanics,PDE theory, signal and image processing. Different quantifiers have been proposedto measure the local regularity of a function. In this paper we present a new quantifier of local regularity of a signal: the pointwise wavelet leaders entropy. We define this new measure of regularity by combining the concept of entropy, coming from the information theory and statistical mechanics, with the wavelet leaders coefficients. Also we establish its inverse relation with one of the well-known regularity exponents, the pointwise H¨older exponent. Finally, we apply this methodology to the financial data series of the Dow Jones Industrial Average Index, registered in the period 1928?2011, in order to compare the temporal evolution of the pointwise H¨older exponent and the pointwise wavelet leaders entropy. The analysis reveals that temporal variation of these quantifiers reflects the evolution of the Dow Jones Industrial Average Index and identifies historical crisis events.
publishDate 2012
dc.date.none.fl_str_mv 2012-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/243822
Rosenblatt, Mariel; Serrano, Eduardo Pedro; Figliola, Maria Alejandra; An entropy based in wavelet leaders to quantify the local regularity of a signal and its application to analyze the Dow Jones index; World Scientific; International Journal of Wavelets, Multiresolution and Information Processing; 10; 5; 10-2012; 1-17
0219-6913
CONICET Digital
CONICET
url http://hdl.handle.net/11336/243822
identifier_str_mv Rosenblatt, Mariel; Serrano, Eduardo Pedro; Figliola, Maria Alejandra; An entropy based in wavelet leaders to quantify the local regularity of a signal and its application to analyze the Dow Jones index; World Scientific; International Journal of Wavelets, Multiresolution and Information Processing; 10; 5; 10-2012; 1-17
0219-6913
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1142/S0219691312500488
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv World Scientific
publisher.none.fl_str_mv World Scientific
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.069144

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