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Investment Strategies Optimization based on a SAX-GA Methodology

  • Book
  • © 2013

Overview

Authors:
  1. António M.L. Canelas

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

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  2. Rui F.M.F. Neves

    1. Instituto de Telecomunicações, Lisboa, Portugal

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  3. Nuno C.G. Horta

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

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  • Presents a new computational finance approach combining SAX and GA
  • Shows soft computing and computational intelligence as solutions for financial markets
  • Case studies presented help identifying the investment strategy to apply in different situations
  • Includes supplementary material: sn.pub/extras

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 (5 chapters)

  1. Front Matter

    Pages i-xii
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  2. Introduction

    • Antonio M. L. Canelas, Rui F. M. F. Neves, Nuno C. G. Horta
    Pages 1-4

  3. Market Analysis Background and Related Work

    • Antonio M. L. Canelas, Rui F. M. M. Neves, Nuno C. G. Horta
    Pages 5-35

  4. SAX-GA Approach

    • Antonio M. L. Canelas, Rui F. M. F. Neves, Nuno C. G. Horta
    Pages 37-57

  5. Results

    • Antonio M. L. Canelas, Rui F. M. F. Neves, Nuno C. G. Horta
    Pages 59-78

  6. Conclusions and Future Work

    • Antonio M. L. Canelas, Rui F. M. F. Neves, Nuno C. G. Horta
    Pages 79-81
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Keywords

About this book

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.

Reviews

From the reviews:

“The book is accessible by anyone with a broad knowledge of statistics and algorithms, and an interest in finance. The nicely done, comprehensive illustrations make this complicated subject easy to understand, and compensate for the often-clumsy sentence structure. I recommend the book … .” (Martin Gfeller, Computing Reviews, May, 2013)

Authors and Affiliations

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

    António M.L. Canelas, Nuno C.G. Horta

  • Instituto de Telecomunicações, Lisboa, Portugal

    Rui F.M.F. Neves

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