Stock exchange trading using grid pattern optimized by a genetic algorithm with speciation : the case of S & P 500 / Tiago Martins, Rui Neves.
Martins, Tiago.; Neves, Rui.
2021
QA402.5 .M27 2021eb
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Title Stock exchange trading using grid pattern optimized by a genetic algorithm with speciation : the case of S & P 500 / Tiago Martins, Rui Neves.
Author Martins, Tiago.
ISBN 9783030766801 (electronic bk.)
3030766802 (electronic bk.)
9783030766795
DOI https://doi.org/10.1007/978-3-030-76680-1
Published Cham, Switzerland : Springer, 2021.
Copyright ©2021
Language English
Description 1 online resource (xv, 68 pages)
Item Number 10.1007/978-3-030-76680-1 doi
Call Number QA402.5 .M27 2021eb
Dewey Decimal Classification 519.6/25
Summary This book presents a genetic algorithm that optimizes a grid template pattern detector to find the best point to trade in the SP 500. The pattern detector is based on a template using a grid of weights with a fixed size. The template takes in consideration not only the closing price but also the open, high, and low values of the price during the period under testing in contrast to the traditional methods of analysing only the closing price. Each cell of the grid encompasses a score, and these are optimized by an evolutionary genetic algorithm that takes genetic diversity into consideration through a speciation routine, giving time for each individual of the population to be optimized within its own niche. With this method, the system is able to present better results and improves the results compared with other template approaches. The tests considered real data from the stock market and against state-of-the-art solutions, namely the ones using a grid of weights which does not have a fixed size and non-speciated approaches. During the testing period, the presented solution had a return of 21.3% compared to 10.9% of the existing approaches. The use of speciation was able to increase the returns of some results as genetic diversity was taken into consideration.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Added Author Neves, Rui.
Series SpringerBriefs in applied sciences and technology.
Available in Other Form Stock Exchange Trading Using Grid Pattern Optimized by a Genetic Algorithm with Speciation.
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Introduction
Related Work
Architecture
Evaluation
Conclusions and future work.

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