Genetic algorithms and applications for stock trading optimization / by Vivek Kapoor and Shubhamoy Dey.

Format:

Book

Author/Creator:

Kapoor, Vivek, 1974- author.

Dey, Shubhamoy, 1964- author.

Language:

English

Subjects (All):

Stocks--Mathematical models.

Stocks.

Genetic algorithms.

Genetic programming (Computer science).

Physical Description:

25 PDFs (262 pages)

Place of Publication:

Hershey, Pennsylvania : Engineering Science Reference, [2021]

System Details:

Mode of access: World Wide Web.

Summary:

"This book offers an overall general review of internal working of Genetic Algorithms (GAs) in search and optimization, and their use in to find out attractive stock trading strategies"-- Provided by publisher.

Contents:

Section 1. Genetic algorithms, neural networks, and chaos theory. Chapter 1. Introduction to expert systems, fuzzy logic, neural networks, and chaos theory ; Chapter 2. Introduction to biologically inspired algorithms ; Chapter 3. Introduction to genetic algorithms in search and optimization ; Chapter 4. Genetic algorithms (GAs) and their mathematical foundations

Section 2. Genetic algorithms theory and its working. Chapter 5. Genetic algorithm (GA) methodology and its internal working ; Chapter 6. Understanding genetic algorithm (GA) operators step by step ; Chapter 7. Operator control parameters and fine tuning of genetic algorithms (GAs) ; Chapter 8. Advance GA operators and techniques in search and optimization

Section 3. Genetic algorithms in finance. Chapter 9. Genetic algorithms (GAs) and stock trading systems ; Chapter 10. Synergistic market analysis, technical analysis, and various indicators ; Chapter 11. Using genetic algorithms to develop investment strategies ; Chapter 12. Developing a single indicator or multiple indicator market timing system

Section 4. Genetic algorithms in other areas. Chapter 13. Some other applications of genetic algorithms (GAs) ; Chapter 14. Introduction to some other nature-inspired algorithms.

Notes:

Description based on print version record.

Includes bibliographical references and index.

ISBN:

9781799841067

OCLC:

1260710441