Previsão do mercado acionário por meio de redes neurais MLP e redes neurais Kohonen em período de crise econômica
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional Manancial UFSM |
Texto Completo: | http://repositorio.ufsm.br/handle/1/4651 |
Resumo: | Fluctuations in the stock market through economic crises, risks of deflation and liquidity traps are critical in the analysis of risk, which cause discrepancies in the execution of a particular scope in the equities market. The crisis in subprime insolvency in 2007/2008 which had a major impact on financial markets founded further discussions in relation to risk control in the decision making of investors. In the stock market risk analysis seeks to assist the investor in making decisions, for it makes use of statistical methods and tools to try to predict market movements. Based on these and previous statements in order to assist investors in making decisions through an economic crisis, this is an exploratory study aimed to develop and train two neural networks with differentiated learning without the problem of "black box" methods to compare which of the two has better forecast in periods of economic crisis. As input variables for the neural networks used the return of the volume of weekly Ibovespa in the period 12/08/2002 to 30/05/2011 and a setup developed from the Elliott Wave Theory. That is, these two neural networks were developed, trained and validated to predict market movements when it presents oscillations from an economic crisis. As mentioned earlier to validate the study compared the power of explanation of two methods before a point of probable attack. We conclude, therefore, that the analogy made for the creation of the theory of Elliott wave theory of psychological behavior of the masses and the Fibonacci sequence proved unable to provide for oscillations of the market in a series corresponding to an economic crisis. It was concluded, too, that neural networks with unsupervised learning using temporal variables as input variables has a higher prediction in training, but lower than most crucial step in the validation of systems. |
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2017-04-062017-04-062013-08-28MIRANDA, André Pacheco. Stock market forecast through ann MLP and Kohonen ann at time of economic crisis. 2013. 105 f. Dissertação (Mestrado em Administração) - Universidade Federal de Santa Maria, Santa Maria, 2013.http://repositorio.ufsm.br/handle/1/4651Fluctuations in the stock market through economic crises, risks of deflation and liquidity traps are critical in the analysis of risk, which cause discrepancies in the execution of a particular scope in the equities market. The crisis in subprime insolvency in 2007/2008 which had a major impact on financial markets founded further discussions in relation to risk control in the decision making of investors. In the stock market risk analysis seeks to assist the investor in making decisions, for it makes use of statistical methods and tools to try to predict market movements. Based on these and previous statements in order to assist investors in making decisions through an economic crisis, this is an exploratory study aimed to develop and train two neural networks with differentiated learning without the problem of "black box" methods to compare which of the two has better forecast in periods of economic crisis. As input variables for the neural networks used the return of the volume of weekly Ibovespa in the period 12/08/2002 to 30/05/2011 and a setup developed from the Elliott Wave Theory. That is, these two neural networks were developed, trained and validated to predict market movements when it presents oscillations from an economic crisis. As mentioned earlier to validate the study compared the power of explanation of two methods before a point of probable attack. We conclude, therefore, that the analogy made for the creation of the theory of Elliott wave theory of psychological behavior of the masses and the Fibonacci sequence proved unable to provide for oscillations of the market in a series corresponding to an economic crisis. It was concluded, too, that neural networks with unsupervised learning using temporal variables as input variables has a higher prediction in training, but lower than most crucial step in the validation of systems.As oscilações no mercado acionário por meio de crises econômicas, riscos de deflação e armadilhas de liquidez são pontos críticos na análise de risco, que ocasionam discrepâncias na execução de um determinado escopo no mercado de renda variável. A crise da inadimplência do subprime em 2007/2008 que obteve uma das maiores repercussões nos mercados financeiros fundou novas discussões em relação ao controle de risco na tomada de decisão do investidor. No mercado acionário, a análise de risco busca auxiliar o investidor na tomada de decisões, para isso utiliza-se de ferramentas e métodos estatísticos para tentar predizer os movimentos do mercado. Com base nestas afirmações anteriores e com o intuito de auxiliar o investidor na tomada de decisão mediante a uma crise econômica, este trabalho, do tipo exploratório, objetivou-se desenvolver e treinar duas redes neurais com aprendizados diferenciados sem o problema da caixa preta dos métodos a fim de comparar quais das duas tem melhor previsão em períodos de crises econômicas. Como variáveis de entrada para as redes neurais utilizou-se o retorno do volume semanais do Ibovespa no período de 12/08/2002 até 30/05/2011 e um setup desenvolvido a partir da Teoria das Ondas de Elliott. Ou seja, estas duas redes neurais foram desenvolvidas, treinadas e validadas para antever os movimentos do mercado quando este apresentar oscilações provenientes de uma crise econômica. Como mencionado anteriormente para validar o estudo, foi comparado o poder de explicação dos dois métodos, antes de um ponto de uma provável crise. Conclui-se, portanto, que a analogia feita para a criação da teoria das ondas de Elliott entre a teoria do comportamento psicológico das massas e a seqüência de Fibonacci se mostrou incapaz de prever oscilações do mercado em uma série correspondente a uma crise econômica. Conclui-se, também, que redes neurais com aprendizados não supervisionados que utilizam variáveis temporais como variáveis de entrada tem a previsão superior no treinamento, mas inferiores na etapa mais determinante a validação das redes.application/pdfporUniversidade Federal de Santa MariaPrograma de Pós-Graduação em AdministraçãoUFSMBRAdministraçãoRedes neuraisCrises econômicasAnálise técnicaNeural networksEconomic crisisTechnical analysisCNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAOPrevisão do mercado acionário por meio de redes neurais MLP e redes neurais Kohonen em período de crise econômicaStock market forecast through ann MLP and Kohonen ann at time of economic crisisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisLopes, Luis Felipe Diashttp://lattes.cnpq.br/1074372911061770Köhler, Viviane Cátiahttp://lattes.cnpq.br/5973417845755750Ceretta, Paulo Sergiohttp://lattes.cnpq.br/3049029014914257http://lattes.cnpq.br/3170208303023200Miranda, André Pacheco6002000000064003003003003001dc759c3-23ad-4b07-ab5e-be9634c1de063f25537d-9a37-46b0-9422-02b0312cd93f4ec91eb7-5288-4886-95ce-858a31b8b382b9cd97ac-6e5e-49bc-b5fe-bb7d2a767fd3info:eu-repo/semantics/openAccessreponame:Repositório Institucional Manancial UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINALMIRANDA, ANDRE PACHECO.pdfapplication/pdf2434541http://repositorio.ufsm.br/bitstream/1/4651/1/MIRANDA%2c%20ANDRE%20PACHECO.pdfa3475ccc9404680abb4fcbe12b080b4cMD51TEXTMIRANDA, ANDRE PACHECO.pdf.txtMIRANDA, ANDRE PACHECO.pdf.txtExtracted texttext/plain208252http://repositorio.ufsm.br/bitstream/1/4651/2/MIRANDA%2c%20ANDRE%20PACHECO.pdf.txtbdfa657f08b04978023143d6b3c736aaMD52THUMBNAILMIRANDA, ANDRE PACHECO.pdf.jpgMIRANDA, ANDRE PACHECO.pdf.jpgIM Thumbnailimage/jpeg5032http://repositorio.ufsm.br/bitstream/1/4651/3/MIRANDA%2c%20ANDRE%20PACHECO.pdf.jpg7ea590e5eb513012d88ba47a298a8fd9MD531/46512023-06-13 14:15:06.925oai:repositorio.ufsm.br:1/4651Repositório Institucionalhttp://repositorio.ufsm.br/PUBhttp://repositorio.ufsm.br/oai/requestouvidoria@ufsm.bropendoar:39132023-06-13T17:15:06Repositório Institucional Manancial UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.por.fl_str_mv |
Previsão do mercado acionário por meio de redes neurais MLP e redes neurais Kohonen em período de crise econômica |
dc.title.alternative.eng.fl_str_mv |
Stock market forecast through ann MLP and Kohonen ann at time of economic crisis |
title |
Previsão do mercado acionário por meio de redes neurais MLP e redes neurais Kohonen em período de crise econômica |
spellingShingle |
Previsão do mercado acionário por meio de redes neurais MLP e redes neurais Kohonen em período de crise econômica Miranda, André Pacheco Redes neurais Crises econômicas Análise técnica Neural networks Economic crisis Technical analysis CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO |
title_short |
Previsão do mercado acionário por meio de redes neurais MLP e redes neurais Kohonen em período de crise econômica |
title_full |
Previsão do mercado acionário por meio de redes neurais MLP e redes neurais Kohonen em período de crise econômica |
title_fullStr |
Previsão do mercado acionário por meio de redes neurais MLP e redes neurais Kohonen em período de crise econômica |
title_full_unstemmed |
Previsão do mercado acionário por meio de redes neurais MLP e redes neurais Kohonen em período de crise econômica |
title_sort |
Previsão do mercado acionário por meio de redes neurais MLP e redes neurais Kohonen em período de crise econômica |
author |
Miranda, André Pacheco |
author_facet |
Miranda, André Pacheco |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Lopes, Luis Felipe Dias |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/1074372911061770 |
dc.contributor.referee1.fl_str_mv |
Köhler, Viviane Cátia |
dc.contributor.referee1Lattes.fl_str_mv |
http://lattes.cnpq.br/5973417845755750 |
dc.contributor.referee2.fl_str_mv |
Ceretta, Paulo Sergio |
dc.contributor.referee2Lattes.fl_str_mv |
http://lattes.cnpq.br/3049029014914257 |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/3170208303023200 |
dc.contributor.author.fl_str_mv |
Miranda, André Pacheco |
contributor_str_mv |
Lopes, Luis Felipe Dias Köhler, Viviane Cátia Ceretta, Paulo Sergio |
dc.subject.por.fl_str_mv |
Redes neurais Crises econômicas Análise técnica |
topic |
Redes neurais Crises econômicas Análise técnica Neural networks Economic crisis Technical analysis CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO |
dc.subject.eng.fl_str_mv |
Neural networks Economic crisis Technical analysis |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO |
description |
Fluctuations in the stock market through economic crises, risks of deflation and liquidity traps are critical in the analysis of risk, which cause discrepancies in the execution of a particular scope in the equities market. The crisis in subprime insolvency in 2007/2008 which had a major impact on financial markets founded further discussions in relation to risk control in the decision making of investors. In the stock market risk analysis seeks to assist the investor in making decisions, for it makes use of statistical methods and tools to try to predict market movements. Based on these and previous statements in order to assist investors in making decisions through an economic crisis, this is an exploratory study aimed to develop and train two neural networks with differentiated learning without the problem of "black box" methods to compare which of the two has better forecast in periods of economic crisis. As input variables for the neural networks used the return of the volume of weekly Ibovespa in the period 12/08/2002 to 30/05/2011 and a setup developed from the Elliott Wave Theory. That is, these two neural networks were developed, trained and validated to predict market movements when it presents oscillations from an economic crisis. As mentioned earlier to validate the study compared the power of explanation of two methods before a point of probable attack. We conclude, therefore, that the analogy made for the creation of the theory of Elliott wave theory of psychological behavior of the masses and the Fibonacci sequence proved unable to provide for oscillations of the market in a series corresponding to an economic crisis. It was concluded, too, that neural networks with unsupervised learning using temporal variables as input variables has a higher prediction in training, but lower than most crucial step in the validation of systems. |
publishDate |
2013 |
dc.date.issued.fl_str_mv |
2013-08-28 |
dc.date.accessioned.fl_str_mv |
2017-04-06 |
dc.date.available.fl_str_mv |
2017-04-06 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
MIRANDA, André Pacheco. Stock market forecast through ann MLP and Kohonen ann at time of economic crisis. 2013. 105 f. Dissertação (Mestrado em Administração) - Universidade Federal de Santa Maria, Santa Maria, 2013. |
dc.identifier.uri.fl_str_mv |
http://repositorio.ufsm.br/handle/1/4651 |
identifier_str_mv |
MIRANDA, André Pacheco. Stock market forecast through ann MLP and Kohonen ann at time of economic crisis. 2013. 105 f. Dissertação (Mestrado em Administração) - Universidade Federal de Santa Maria, Santa Maria, 2013. |
url |
http://repositorio.ufsm.br/handle/1/4651 |
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