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Compound distributions for financial returns

In this paper, we propose six Student’s t based compound distributions where the scale parameter is randomized using functional forms of the half normal, Fréchet, Lomax, Burr III, inverse gamma and generalized gamma distributions. For each of the proposed distribution, we give expressions for the pr...

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Autores principales: Afuecheta, Emmanuel, Semeyutin, Artur, Chan, Stephen, Nadarajah, Saralees, Andrés Pérez Ruiz, Diego
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7531861/
https://www.ncbi.nlm.nih.gov/pubmed/33006975
http://dx.doi.org/10.1371/journal.pone.0239652
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author Afuecheta, Emmanuel
Semeyutin, Artur
Chan, Stephen
Nadarajah, Saralees
Andrés Pérez Ruiz, Diego
author_facet Afuecheta, Emmanuel
Semeyutin, Artur
Chan, Stephen
Nadarajah, Saralees
Andrés Pérez Ruiz, Diego
author_sort Afuecheta, Emmanuel
collection PubMed
description In this paper, we propose six Student’s t based compound distributions where the scale parameter is randomized using functional forms of the half normal, Fréchet, Lomax, Burr III, inverse gamma and generalized gamma distributions. For each of the proposed distribution, we give expressions for the probability density function, cumulative distribution function, moments and characteristic function. GARCH models with innovations taken to follow the compound distributions are fitted to the data using the method of maximum likelihood. For the sample data considered, we see that all but two of the proposed distributions perform better than two popular distributions. Finally, we perform a simulation study to examine the accuracy of the best performing model.
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spelling pubmed-75318612020-10-08 Compound distributions for financial returns Afuecheta, Emmanuel Semeyutin, Artur Chan, Stephen Nadarajah, Saralees Andrés Pérez Ruiz, Diego PLoS One Research Article In this paper, we propose six Student’s t based compound distributions where the scale parameter is randomized using functional forms of the half normal, Fréchet, Lomax, Burr III, inverse gamma and generalized gamma distributions. For each of the proposed distribution, we give expressions for the probability density function, cumulative distribution function, moments and characteristic function. GARCH models with innovations taken to follow the compound distributions are fitted to the data using the method of maximum likelihood. For the sample data considered, we see that all but two of the proposed distributions perform better than two popular distributions. Finally, we perform a simulation study to examine the accuracy of the best performing model. Public Library of Science 2020-10-02 /pmc/articles/PMC7531861/ /pubmed/33006975 http://dx.doi.org/10.1371/journal.pone.0239652 Text en © 2020 Afuecheta et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Afuecheta, Emmanuel
Semeyutin, Artur
Chan, Stephen
Nadarajah, Saralees
Andrés Pérez Ruiz, Diego
Compound distributions for financial returns
title Compound distributions for financial returns
title_full Compound distributions for financial returns
title_fullStr Compound distributions for financial returns
title_full_unstemmed Compound distributions for financial returns
title_short Compound distributions for financial returns
title_sort compound distributions for financial returns
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7531861/
https://www.ncbi.nlm.nih.gov/pubmed/33006975
http://dx.doi.org/10.1371/journal.pone.0239652
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