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Genetic Algorithms and Applications for Stock Trading Optimization (Paperback) Loot Price: R4,997
Discovery Miles 49 970
Genetic Algorithms and Applications for Stock Trading Optimization (Paperback): Vivek Kapoor, Shubhamoy Dey

Genetic Algorithms and Applications for Stock Trading Optimization (Paperback)

Vivek Kapoor, Shubhamoy Dey

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Loot Price R4,997 Discovery Miles 49 970 | Repayment Terms: R468 pm x 12*

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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.

General

Imprint: Business Science Reference
Country of origin: United States
Release date: July 2021
First published: 2021
Authors: Vivek Kapoor • Shubhamoy Dey
Dimensions: 254 x 178mm (L x W)
Format: Paperback
Pages: 315
ISBN-13: 978-1-79987-077-7
Categories: Books > Business & Economics > Finance & accounting > Finance > Investment & securities > General
Books > Money & Finance > Investment & securities > General
LSN: 1-79987-077-4
Barcode: 9781799870777

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