On the existence of an optimal estimation window for risk measures
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Data de Publicação: | 2016 |
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Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/142274 |
Resumo: | We investigate whether there can exist an optimal estimation window for financial risk measures. Accordingly, we propose a procedure that achieves optimal estimation window by minimizing estimation bias. Using results from a Monte Carlo simulation for Value at Risk and Expected Shortfall in distinct scenarios, we conclude that the optimal length for the estimation window is not random but has very clear patterns. Our findings can contribute to the literature, as studies have typically neglected the estimation window choice or relied on arbitrary choices. Citation: |
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Righi, Marcelo BruttiCeretta, Paulo Sérgio2016-06-04T02:09:19Z20161545-2921http://hdl.handle.net/10183/142274000988443We investigate whether there can exist an optimal estimation window for financial risk measures. Accordingly, we propose a procedure that achieves optimal estimation window by minimizing estimation bias. Using results from a Monte Carlo simulation for Value at Risk and Expected Shortfall in distinct scenarios, we conclude that the optimal length for the estimation window is not random but has very clear patterns. Our findings can contribute to the literature, as studies have typically neglected the estimation window choice or relied on arbitrary choices. Citation:application/pdfengEconomics bulletin. Nashville. Vol. 36, n. 1 (2016), p. 1-9Risco financeiroBolsa de valoresOn the existence of an optimal estimation window for risk measuresEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSORIGINAL000988443.pdf000988443.pdfTexto completo (inglês)application/pdf518162http://www.lume.ufrgs.br/bitstream/10183/142274/1/000988443.pdf6dad97705a9a30a5ad61c3b49b57e2b5MD51TEXT000988443.pdf.txt000988443.pdf.txtExtracted Texttext/plain14967http://www.lume.ufrgs.br/bitstream/10183/142274/2/000988443.pdf.txt6de7cd553b0860c9be244e3b87915929MD52THUMBNAIL000988443.pdf.jpg000988443.pdf.jpgGenerated Thumbnailimage/jpeg1426http://www.lume.ufrgs.br/bitstream/10183/142274/3/000988443.pdf.jpg099007b2e557de66964fdc5bfe2d910eMD5310183/1422742021-09-18 04:41:31.143268oai:www.lume.ufrgs.br:10183/142274Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2021-09-18T07:41:31Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
On the existence of an optimal estimation window for risk measures |
title |
On the existence of an optimal estimation window for risk measures |
spellingShingle |
On the existence of an optimal estimation window for risk measures Righi, Marcelo Brutti Risco financeiro Bolsa de valores |
title_short |
On the existence of an optimal estimation window for risk measures |
title_full |
On the existence of an optimal estimation window for risk measures |
title_fullStr |
On the existence of an optimal estimation window for risk measures |
title_full_unstemmed |
On the existence of an optimal estimation window for risk measures |
title_sort |
On the existence of an optimal estimation window for risk measures |
author |
Righi, Marcelo Brutti |
author_facet |
Righi, Marcelo Brutti Ceretta, Paulo Sérgio |
author_role |
author |
author2 |
Ceretta, Paulo Sérgio |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Righi, Marcelo Brutti Ceretta, Paulo Sérgio |
dc.subject.por.fl_str_mv |
Risco financeiro Bolsa de valores |
topic |
Risco financeiro Bolsa de valores |
description |
We investigate whether there can exist an optimal estimation window for financial risk measures. Accordingly, we propose a procedure that achieves optimal estimation window by minimizing estimation bias. Using results from a Monte Carlo simulation for Value at Risk and Expected Shortfall in distinct scenarios, we conclude that the optimal length for the estimation window is not random but has very clear patterns. Our findings can contribute to the literature, as studies have typically neglected the estimation window choice or relied on arbitrary choices. Citation: |
publishDate |
2016 |
dc.date.accessioned.fl_str_mv |
2016-06-04T02:09:19Z |
dc.date.issued.fl_str_mv |
2016 |
dc.type.driver.fl_str_mv |
Estrangeiro info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
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article |
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http://hdl.handle.net/10183/142274 |
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1545-2921 |
dc.identifier.nrb.pt_BR.fl_str_mv |
000988443 |
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1545-2921 000988443 |
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http://hdl.handle.net/10183/142274 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Economics bulletin. Nashville. Vol. 36, n. 1 (2016), p. 1-9 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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