Genetic Algorithms and Applications for Stock Trading Optimization eBook

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Genetic algorithms (GAs) are based on Darwin’s theory of natural selection and survival of the fittest. They are designed to competently look for solutions to big and multifaceted problems. Genetic algorithms are wide groups of interrelated events with divided steps. Each step has dissimilarities, which leads to a broad range of connected actions. Genetic algorithms are used to improve trading systems, such as to optimize a trading rule or parameters of a predefined multiple indicator market trading system. Genetic Algorithms and Applications for Stock Trading Optimization is a complete reference source to genetic algorithms that explains how they might be used to find trading strategies, as well as their use in search and optimization. It covers the functions of genetic algorithms internally, computer implementation of pseudo-code of genetic algorithms in C , technical analysis for stock market forecasting, and research outcomes that apply in the stock trading system. This book is ideal for computer scientists, IT specialists, data scientists, managers, executives, professionals, academicians, researchers, graduate-level programs, research programs, and post-graduate students of engineering and science.

Additional ISBNs
9781799841067

Genetic Algorithms and Applications for Stock Trading Optimization is written by Vivek Kapoor; Shubhamoy Dey and published by Engineering Science Reference. The Digital and eTextbook ISBNs for Genetic Algorithms and Applications for Stock Trading Optimization are 9781799841074, 1799841073 and the print ISBNs are 9781799841050, 1799841057. Additional ISBNs for this eTextbook include 9781799841067.