Previsão de retornos intradiários através de regressões usando funções-núcleo

Detalhes bibliográficos
Autor(a) principal: Pereira, Pedro L. Valls
Data de Publicação: 2009
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Institucional do FGV (FGV Repositório Digital)
Texto Completo: http://hdl.handle.net/10438/2662
Resumo: The contributions of this paper are twofold. First we discuss and apply a method for the evaluation of non linear regressions in forecasting intraday returns of Brazilian stocks, in order to maximize the return of a simulated trading portfolio. Second, Kernel regressions associated with Nearest Neighbors sample partitioning are carried out. Some independent variables are technical indicators, which parameters are optimized in-the-sample. The results are positive as a trading strategy and outperformed by a small difference the linear autoregression benchmark model in a quartile per quartile analysis
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spelling Pereira, Pedro L. VallsEscolas::EESP2009-06-10T14:21:11Z2009-06-10T14:21:11Z2009-06-10http://hdl.handle.net/10438/2662The contributions of this paper are twofold. First we discuss and apply a method for the evaluation of non linear regressions in forecasting intraday returns of Brazilian stocks, in order to maximize the return of a simulated trading portfolio. Second, Kernel regressions associated with Nearest Neighbors sample partitioning are carried out. Some independent variables are technical indicators, which parameters are optimized in-the-sample. The results are positive as a trading strategy and outperformed by a small difference the linear autoregression benchmark model in a quartile per quartile analysisAs contribuições deste artigo são duas. A primeira, um método de avaliação de regressões não lineares para a previsão de retornos intradiários de ações no mercado brasileiro é discutido e aplicado, com o objetivo de maximizar o retorno de um portfólio simulado de compras e vendas. A segunda, regressões usando funções-núcleo associadas ao particionamento da amostra por vizinhos mais próximos são realizadas. Algumas variáveis independentes utilizadas são indicadores técnicos, cujos parâmetros são otimizados dentro da amostra de estimação. Os resultados alcançados são positivos e superam, em uma análise quartil a quartil, os resultados produzidos por um modelo benchmark de autorregressão linearporTextos para discussão ; 178Intraday returnsKernel regressionNearest neighborsTechnical indicatorsModelos econométricosEconomiaEconomiaPrevisão de retornos intradiários através de regressões usando funções-núcleoinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlereponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVinfo:eu-repo/semantics/openAccessORIGINALTD 178 Pedro Valls.pdfTD 178 Pedro Valls.pdfapplication/pdf289084https://repositorio.fgv.br/bitstreams/46c0242d-e55b-4515-ba99-9684d736a0db/downloadce4bab97bef53b76c4bb1c9c85728ac0MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81838https://repositorio.fgv.br/bitstreams/33b8a35f-9219-41e9-a943-353ec8bbeac3/download42edde7bb90bf0beec39df2db7fd37f4MD52TEXTTD 178 Pedro Valls.pdf.txtTD 178 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dc.title.por.fl_str_mv Previsão de retornos intradiários através de regressões usando funções-núcleo
title Previsão de retornos intradiários através de regressões usando funções-núcleo
spellingShingle Previsão de retornos intradiários através de regressões usando funções-núcleo
Pereira, Pedro L. Valls
Intraday returns
Kernel regression
Nearest neighbors
Technical indicators
Modelos econométricos
Economia
Economia
title_short Previsão de retornos intradiários através de regressões usando funções-núcleo
title_full Previsão de retornos intradiários através de regressões usando funções-núcleo
title_fullStr Previsão de retornos intradiários através de regressões usando funções-núcleo
title_full_unstemmed Previsão de retornos intradiários através de regressões usando funções-núcleo
title_sort Previsão de retornos intradiários através de regressões usando funções-núcleo
author Pereira, Pedro L. Valls
author_facet Pereira, Pedro L. Valls
author_role author
dc.contributor.unidadefgv.por.fl_str_mv Escolas::EESP
dc.contributor.author.fl_str_mv Pereira, Pedro L. Valls
dc.subject.eng.fl_str_mv Intraday returns
Kernel regression
Nearest neighbors
Technical indicators
topic Intraday returns
Kernel regression
Nearest neighbors
Technical indicators
Modelos econométricos
Economia
Economia
dc.subject.por.fl_str_mv Modelos econométricos
dc.subject.area.por.fl_str_mv Economia
dc.subject.bibliodata.por.fl_str_mv Economia
description The contributions of this paper are twofold. First we discuss and apply a method for the evaluation of non linear regressions in forecasting intraday returns of Brazilian stocks, in order to maximize the return of a simulated trading portfolio. Second, Kernel regressions associated with Nearest Neighbors sample partitioning are carried out. Some independent variables are technical indicators, which parameters are optimized in-the-sample. The results are positive as a trading strategy and outperformed by a small difference the linear autoregression benchmark model in a quartile per quartile analysis
publishDate 2009
dc.date.accessioned.fl_str_mv 2009-06-10T14:21:11Z
dc.date.available.fl_str_mv 2009-06-10T14:21:11Z
dc.date.issued.fl_str_mv 2009-06-10
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10438/2662
url http://hdl.handle.net/10438/2662
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dc.relation.ispartofseries.por.fl_str_mv Textos para discussão ; 178
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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