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Parallel Genetic Algorithms for Financial Pattern Discovery Using GPUs

  • Book
  • © 2018

Overview

Authors:
  1. João Baúto

    1. Instituto Superior Técnico, Instituto de Telecomunicações, Lisbon, Portugal

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  2. Rui Neves

    1. Instituto Superior Técnico, Instituto de Telecomunicações, Lisbon, Portugal

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  3. Nuno Horta

    1. Instituto Superior Técnico, Instituto de Telecomunicações, Lisbon, Portugal

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  • Describes in deep the efficient implementation of SAX/GA algorithm in GPU
  • Presents an algorithm useful to optimize market trading strategies
  • Useful for computational finance applications

Part of the book series: SpringerBriefs in Applied Sciences and Technology (BRIEFSAPPLSCIENCES)

Part of the book sub series: SpringerBriefs in Computational Intelligence (BRIEFSINTELL)

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-xiv
    Download chapter PDF

  2. Introduction

    • João Baúto, Rui Neves, Nuno Horta
    Pages 1-3

  3. Background

    • João Baúto, Rui Neves, Nuno Horta
    Pages 5-20

  4. State-of-the-Art in Pattern Recognition Techniques

    • João Baúto, Rui Neves, Nuno Horta
    Pages 21-32

  5. SAX/GA CPU Approach

    • João Baúto, Rui Neves, Nuno Horta
    Pages 33-44

  6. GPU-Accelerated SAX/GA

    • João Baúto, Rui Neves, Nuno Horta
    Pages 45-66

  7. Results

    • João Baúto, Rui Neves, Nuno Horta
    Pages 67-88

  8. Conclusions and Future Work

    • João Baúto, Rui Neves, Nuno Horta
    Pages 89-91
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Keywords

About this book

This Brief presents a study of SAX/GA, an algorithm to optimize market trading strategies, to understand how the sequential implementation of SAX/GA and genetic operators work to optimize possible solutions. This study is later used as the baseline for the development of parallel techniques capable of exploring the identified points of parallelism that simply focus on accelerating the heavy duty fitness function to a full GPU accelerated GA. 

Authors and Affiliations

  • Instituto Superior Técnico, Instituto de Telecomunicações, Lisbon, Portugal

    João Baúto, Rui Neves, Nuno Horta

About the authors

João Baúto works at Fundacao Champalimaud in Lisbon, Portugal. He implements high performance computing tools applied to neuroscience and cancer research.

Rui Ferreira Neves is a professor at Instituto Superior Técnico, Portugal. His research activity comprises evolutionary computation and pattern matching applied to the financial markets, sensor networks, embedded systems and mixed signal integrated circuits.


Nuno Horta is the Head of the Integrated Circuits Group, Instituto de Telecomunicacoes, Portugal. His reseach interests are mainly in analog and mixed-sgnal IC design, analog IC design automation, soft computing and data science.

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