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Datasets for testing the performances of jump diffusion models

This article contains datasets related to the research article titled a novel jump diffusion model based on SGT distribution and its applications (”A novel jump diffusion model based on SGT distribution and its applications” (W.J. Xu, G.F. Liu, H.Y. Li, 2016) [1]). The datasets contain continuous co...

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Detalles Bibliográficos
Autores principales: Xu, Weijun, Liu, Guifang, Li, Hongyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5144646/
https://www.ncbi.nlm.nih.gov/pubmed/27981199
http://dx.doi.org/10.1016/j.dib.2016.11.014
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author Xu, Weijun
Liu, Guifang
Li, Hongyi
author_facet Xu, Weijun
Liu, Guifang
Li, Hongyi
author_sort Xu, Weijun
collection PubMed
description This article contains datasets related to the research article titled a novel jump diffusion model based on SGT distribution and its applications (”A novel jump diffusion model based on SGT distribution and its applications” (W.J. Xu, G.F. Liu, H.Y. Li, 2016) [1]). The datasets contain continuous composite daily percentage return values which are computed from the daily closing prices. Firstly, we describe statistical properties of the datasets. Then, the datasets are split into two samples, the in-sample data and out-of-sample data. The datasets can be used as benchmarks for testing the performances of jump diffusion models.
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spelling pubmed-51446462016-12-15 Datasets for testing the performances of jump diffusion models Xu, Weijun Liu, Guifang Li, Hongyi Data Brief Data Article This article contains datasets related to the research article titled a novel jump diffusion model based on SGT distribution and its applications (”A novel jump diffusion model based on SGT distribution and its applications” (W.J. Xu, G.F. Liu, H.Y. Li, 2016) [1]). The datasets contain continuous composite daily percentage return values which are computed from the daily closing prices. Firstly, we describe statistical properties of the datasets. Then, the datasets are split into two samples, the in-sample data and out-of-sample data. The datasets can be used as benchmarks for testing the performances of jump diffusion models. Elsevier 2016-11-10 /pmc/articles/PMC5144646/ /pubmed/27981199 http://dx.doi.org/10.1016/j.dib.2016.11.014 Text en © 2017 Published by Elsevier Inc. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Xu, Weijun
Liu, Guifang
Li, Hongyi
Datasets for testing the performances of jump diffusion models
title Datasets for testing the performances of jump diffusion models
title_full Datasets for testing the performances of jump diffusion models
title_fullStr Datasets for testing the performances of jump diffusion models
title_full_unstemmed Datasets for testing the performances of jump diffusion models
title_short Datasets for testing the performances of jump diffusion models
title_sort datasets for testing the performances of jump diffusion models
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5144646/
https://www.ncbi.nlm.nih.gov/pubmed/27981199
http://dx.doi.org/10.1016/j.dib.2016.11.014
work_keys_str_mv AT xuweijun datasetsfortestingtheperformancesofjumpdiffusionmodels
AT liuguifang datasetsfortestingtheperformancesofjumpdiffusionmodels
AT lihongyi datasetsfortestingtheperformancesofjumpdiffusionmodels