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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
Descripción
Sumario: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.