Reaction trend system with GARCH quantiles as action points[Formula presented]
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.eswa.2022.116750 http://hdl.handle.net/11449/234290 |
Resumo: | Most trading systems developed from technical indicators are designed to operate in either trending or non-trending markets but they are rarely useful for both markets. A reaction trend system allows operations in both markets. In this study, we improve the calculus of four action points using a statistical volatility model and then replace the action points with those derived from GARCH quantiles. Although the proposed system is more advanced, it maintains the same operational logic as the method proposed by Wilder. Empirical tests on various assets suggest that the novel method performs better. Finally, we compare the performance of our proposed system with previous studies that analysed assets in different markets and regions. Our system has been proven consistently competitive in all situations. |
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Repositório Institucional da UNESP |
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Reaction trend system with GARCH quantiles as action points[Formula presented]prediction of price intervalsStatistical volatility modelTechnical analysisWilder's trading strategiesMost trading systems developed from technical indicators are designed to operate in either trending or non-trending markets but they are rarely useful for both markets. A reaction trend system allows operations in both markets. In this study, we improve the calculus of four action points using a statistical volatility model and then replace the action points with those derived from GARCH quantiles. Although the proposed system is more advanced, it maintains the same operational logic as the method proposed by Wilder. Empirical tests on various assets suggest that the novel method performs better. Finally, we compare the performance of our proposed system with previous studies that analysed assets in different markets and regions. Our system has been proven consistently competitive in all situations.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)University of Brasília (UnB) Department of Statistics Campus Darcy Ribeiro Brasília–DF 70910–900São Paulo State University (UNESP) Institute of Biosciences Humanities and Exact Sciences São José do Rio Preto–SP 15054–000Federal University of Uberlândia (UFU) School of Business and Management Uberlândia–MG 38400–902São Paulo State University (UNESP) Institute of Biosciences Humanities and Exact Sciences São José do Rio Preto–SP 15054–000FAPESP: 2013/07375-0FAPESP: 2016/10431-7CNPq: 435173/2018-970910–900Universidade Estadual Paulista (UNESP)Universidade Federal de Uberlândia (UFU)Fiorucci, Jose AugustoSilva, Geraldo Nunes [UNESP]Barboza, Flavio2022-05-01T15:46:14Z2022-05-01T15:46:14Z2022-07-15info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1016/j.eswa.2022.116750Expert Systems with Applications, v. 198.0957-4174http://hdl.handle.net/11449/23429010.1016/j.eswa.2022.1167502-s2.0-85126678885Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengExpert Systems with Applicationsinfo:eu-repo/semantics/openAccess2022-05-01T15:46:14Zoai:repositorio.unesp.br:11449/234290Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:52:18.595863Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Reaction trend system with GARCH quantiles as action points[Formula presented] |
title |
Reaction trend system with GARCH quantiles as action points[Formula presented] |
spellingShingle |
Reaction trend system with GARCH quantiles as action points[Formula presented] Fiorucci, Jose Augusto prediction of price intervals Statistical volatility model Technical analysis Wilder's trading strategies |
title_short |
Reaction trend system with GARCH quantiles as action points[Formula presented] |
title_full |
Reaction trend system with GARCH quantiles as action points[Formula presented] |
title_fullStr |
Reaction trend system with GARCH quantiles as action points[Formula presented] |
title_full_unstemmed |
Reaction trend system with GARCH quantiles as action points[Formula presented] |
title_sort |
Reaction trend system with GARCH quantiles as action points[Formula presented] |
author |
Fiorucci, Jose Augusto |
author_facet |
Fiorucci, Jose Augusto Silva, Geraldo Nunes [UNESP] Barboza, Flavio |
author_role |
author |
author2 |
Silva, Geraldo Nunes [UNESP] Barboza, Flavio |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
70910–900 Universidade Estadual Paulista (UNESP) Universidade Federal de Uberlândia (UFU) |
dc.contributor.author.fl_str_mv |
Fiorucci, Jose Augusto Silva, Geraldo Nunes [UNESP] Barboza, Flavio |
dc.subject.por.fl_str_mv |
prediction of price intervals Statistical volatility model Technical analysis Wilder's trading strategies |
topic |
prediction of price intervals Statistical volatility model Technical analysis Wilder's trading strategies |
description |
Most trading systems developed from technical indicators are designed to operate in either trending or non-trending markets but they are rarely useful for both markets. A reaction trend system allows operations in both markets. In this study, we improve the calculus of four action points using a statistical volatility model and then replace the action points with those derived from GARCH quantiles. Although the proposed system is more advanced, it maintains the same operational logic as the method proposed by Wilder. Empirical tests on various assets suggest that the novel method performs better. Finally, we compare the performance of our proposed system with previous studies that analysed assets in different markets and regions. Our system has been proven consistently competitive in all situations. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-05-01T15:46:14Z 2022-05-01T15:46:14Z 2022-07-15 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1016/j.eswa.2022.116750 Expert Systems with Applications, v. 198. 0957-4174 http://hdl.handle.net/11449/234290 10.1016/j.eswa.2022.116750 2-s2.0-85126678885 |
url |
http://dx.doi.org/10.1016/j.eswa.2022.116750 http://hdl.handle.net/11449/234290 |
identifier_str_mv |
Expert Systems with Applications, v. 198. 0957-4174 10.1016/j.eswa.2022.116750 2-s2.0-85126678885 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Expert Systems with Applications |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129560119607296 |