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Título : Retrodicting with the truncated Lévy flight
Autor : Matsushita, Raul Yukihiro
Brom, Pedro Carvalho
Nagata, Mateus Hiro
Silva, Sérgio da
metadata.dc.contributor.affiliation: University of Brasilia, Department of Statistics, Graduate Program in Statistics
University of Brasilia, Graduate Program in Business Administration
University of Brasilia, Department of Statistics, Graduate Program in Statistics
ITAM, Department of Economic
Fderal University of Santa Catarina, Departament of Economic
Federal University of Espirito Santo, Graduate Program in Economics
Assunto:: Voos de Lévy
Dados financeiros
Taxa de câmbio
Fecha de publicación : 2024
Editorial : Elsevier
Citación : MATSUSHITA, Raul Yukihiro et al. Retrodicting with the truncated Lévy flight. Communications in Nonlinear Science and Numerical Simulation, [S.l.], v. 116. Jan. 2023. DOI: https://doi.org/10.1016/j.cnsns.2022.106900. Disponível em: https://www.sciencedirect.com/science/article/pii/S1007570422003872. Acesso em: 13 ago. 2023.
Resumen : There is a point in predicting the past (retrodicting) because we lack information about it. To address this issue, we consider a truncated Lévy flight to model data. We build on the finding that there is a power law between truncation length and standard deviation that connects the bounded past and unbounded future. Even if a truncated Lévy flight cannot predict future extreme events, we argue that it can still be used to model the past. Because we avoid the exact form of the probability density function while allowing its distributional moments, with the exception of the mean, to vary over time, our method is applicable to a wide range of symmetric distributions. We illustrate our point by using US dollar prices in 15 different currencies traded on foreign exchange markets.
metadata.dc.description.unidade: Instituto de Ciências Exatas (IE)
Departamento de Estatística (IE EST)
Faculdade de Economia, Administração, Contabilidade e Gestão de Políticas Públicas (FACE)
metadata.dc.description.ppg: Programa de Pós-Graduação em Estatística
Programa de Pós-Graduação em Administração
DOI: https://doi.org/10.1016/j.cnsns.2022.106900
metadata.dc.relation.publisherversion: https://www.sciencedirect.com/science/article/pii/S1007570422003872?via%3Dihub
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