Parallel Genetic Algorithms for Financial Pattern Discovery Using GPUs

1. Front Matter

   Pages i-xiv

   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

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. 

• computational finance
• pattern recognition techniques
• high performance computing
• data science
• SAX/GA algorithm
• market trading strategies
• quantitative finance

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

  João Baúto, Rui Neves, Nuno Horta

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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