Differential entropy estimation with a Paretian kernel : tail heaviness and smoothing

Matsushita, Raul Yukihiro; Brandão, Helena Santos; Nobre, Iuri Ribeiro; Silva, Sergio da

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Campo DC	Valor	Idioma
dc.contributor.author	Matsushita, Raul Yukihiro	-
dc.contributor.author	Brandão, Helena Santos	-
dc.contributor.author	Nobre, Iuri Ribeiro	-
dc.contributor.author	Silva, Sergio da	-
dc.date.accessioned	2026-02-12T20:28:40Z	-
dc.date.available	2026-02-12T20:28:40Z	-
dc.date.issued	2024-05-25	-
dc.identifier.citation	MATSUSHITA, Raul Yukihiro; BRANDÃO, Helena Santos; NOBRE, Iuri Ribeiro; SILVA, Sergio da. Differential entropy estimation with a Paretian kernel: tail heaviness and smoothing. Physica A: Statistical Mechanics and its Applications, [S.l.], v. 646, e129850, 2025. DOI: https://doi.org/10.1016/j.physa.2024.129850. Disponível em: https://www.sciencedirect.com/science/article/pii/S0378437124003595?via%3Dihub. Acesso em: 12 fev. 2026.	pt_BR
dc.identifier.uri	http://repositorio.unb.br/handle/10482/54052	-
dc.language.iso	eng	pt_BR
dc.publisher	Elsevier	pt_BR
dc.rights	Acesso Restrito	pt_BR
dc.title	Differential entropy estimation with a Paretian kernel : tail heaviness and smoothing	pt_BR
dc.type	Artigo	pt_BR
dc.subject.keyword	Entropia diferencial	pt_BR
dc.subject.keyword	Kernel de Pareto	pt_BR
dc.subject.keyword	Caudas pesadas	pt_BR
dc.identifier.doi	https://doi.org/10.1016/j.physa.2024.129850	pt_BR
dc.relation.publisherversion	https://www.sciencedirect.com/science/article/pii/S0378437124003595?via%3Dihub	pt_BR
dc.description.abstract1	Differential entropy extends the concept of entropy to continuous probability distributions, measuring the uncertainty associated with a continuous random variable. In financial data analysis, accurately estimating differential entropy is pivotal for understanding market dynamics and assessing risk. Traditional methods often fall short when dealing with the heavy-tailed distributions characteristic of financial returns. This paper introduces a novel approach to differential entropy estimation employing a Paretian kernel function adept at handling tail heaviness’s intricacies. By incorporating an additional smoothing parameter, the Pareto exponent, our method offers flexibility in adjusting to light and heavy-tailed distributions. We compare our approach against established estimators through a comprehensive Monte Carlo simulation, demonstrating its superior performance in various scenarios. Applying our method to foreign exchange market data further illustrates its practical utility in identifying stochastic regimes and enhancing financial analysis. Our findings advocate for integrating the Paretian kernel estimator into the toolkit of financial analysts and researchers for a more nuanced understanding of market behavior.	pt_BR
dc.identifier.orcid	https://orcid.org/0000-0001-8864-6356	pt_BR
dc.identifier.orcid	https://orcid.org/0009-0003-8633-5353	pt_BR
dc.identifier.orcid	https://orcid.org/0000-0001-8279-4083	pt_BR
dc.contributor.affiliation	University of Brasilia, Graduate Program in Statistics	pt_BR
dc.contributor.affiliation	University of Brasilia, Graduate Program in Management	pt_BR
dc.contributor.affiliation	University of Brasilia, Graduate Program in Statistics	pt_BR
dc.contributor.affiliation	University of Brasilia, Graduate Program in Management	pt_BR
dc.contributor.affiliation	Federal University of Santa Catarina, Graduate Program in Economics	pt_BR
dc.description.unidade	Instituto de Ciências Exatas (IE)	pt_BR
dc.description.unidade	Departamento de Estatística (IE EST)	pt_BR
dc.description.unidade	Faculdade de Economia, Administração, Contabilidade e Gestão de Políticas Públicas (FACE)	pt_BR
dc.description.unidade	Departamento de Administração (FACE ADM)	pt_BR
dc.description.ppg	Programa de Pós-Graduação em Estatística	pt_BR
dc.description.ppg	Programa de Pós-Graduação em Administração	pt_BR
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