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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/243822
Ver los metadatos del registro completo
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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 Técnicas2025-09-03T10:01:09Zoai: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:34982025-09-03 10:01:09.374CONICET 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 |
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CONICET Digital (CONICET) |
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CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
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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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