Investment Strategies Optimization based on a SAX-GA Methodology

This book presents a new computational finance approach combining a Symbolic Aggregate approXimation (SAX) technique with an optimization kernel based on genetic algorithms (GA). While the SAX representation is used to describe the financial time series, the evolutionary optimization kernel is used...

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Detalles Bibliográficos
Autores principales: Canelas, António M L, Neves, Rui F M F, Horta, Nuno C G
Lenguaje:eng
Publicado: Springer 2013
Materias:
Engineering
Acceso en línea:https://dx.doi.org/10.1007/978-3-642-33110-7
http://cds.cern.ch/record/1500385
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author Canelas, António M L
Neves, Rui F M F
Horta, Nuno C G
author_facet Canelas, António M L
Neves, Rui F M F
Horta, Nuno C G
author_sort Canelas, António M L
collection CERN
description This book presents a new computational finance approach combining a Symbolic Aggregate approXimation (SAX) technique with an optimization kernel based on genetic algorithms (GA). While the SAX representation is used to describe the financial time series, the evolutionary optimization kernel is used in order to identify the most relevant patterns and generate investment rules. The proposed approach considers several different chromosomes structures in order to achieve better results on the trading platform The methodology presented in this book has great potential on investment markets.
id cern-1500385
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2013
publisher Springer
record_format invenio
spelling cern-15003852021-04-22T00:01:00Zdoi:10.1007/978-3-642-33110-7http://cds.cern.ch/record/1500385engCanelas, António M LNeves, Rui F M FHorta, Nuno C GInvestment Strategies Optimization based on a SAX-GA MethodologyEngineeringThis book presents a new computational finance approach combining a Symbolic Aggregate approXimation (SAX) technique with an optimization kernel based on genetic algorithms (GA). While the SAX representation is used to describe the financial time series, the evolutionary optimization kernel is used in order to identify the most relevant patterns and generate investment rules. The proposed approach considers several different chromosomes structures in order to achieve better results on the trading platform The methodology presented in this book has great potential on investment markets.Springeroai:cds.cern.ch:15003852013
spellingShingle Engineering
Canelas, António M L
Neves, Rui F M F
Horta, Nuno C G
Investment Strategies Optimization based on a SAX-GA Methodology
title Investment Strategies Optimization based on a SAX-GA Methodology
title_full Investment Strategies Optimization based on a SAX-GA Methodology
title_fullStr Investment Strategies Optimization based on a SAX-GA Methodology
title_full_unstemmed Investment Strategies Optimization based on a SAX-GA Methodology
title_short Investment Strategies Optimization based on a SAX-GA Methodology
title_sort investment strategies optimization based on a sax-ga methodology
topic Engineering
url https://dx.doi.org/10.1007/978-3-642-33110-7
http://cds.cern.ch/record/1500385
work_keys_str_mv AT canelasantonioml investmentstrategiesoptimizationbasedonasaxgamethodology
AT nevesruifmf investmentstrategiesoptimizationbasedonasaxgamethodology
AT hortanunocg investmentstrategiesoptimizationbasedonasaxgamethodology

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