Genetic Algorithms and Applications for Stock Trading Optimization (Paperback)

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 Promotions
LSN:	1-79987-077-4
Barcode:	9781799870777

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!