Genetic Algorithms and Applications for Stock Trading Optimization
Seiten
2021
Business Science Reference (Verlag)
978-1-7998-4105-0 (ISBN)
Business Science Reference (Verlag)
978-1-7998-4105-0 (ISBN)
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. The book covers the functions of genetic algorithms internally, computer implementation of pseudo-code of genetic algorithms in C++, and technical analysis for stock market forecasting.
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.
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.
Shubhamoy Dey is a professor of information systems at Indian Institute of Management Indore, India. He completed his Ph. D from the School of Computing, University of Leeds, UK, and Master of Technology from Indian Institute of Technology (IITKharagpur). He specializes in Data Mining and has 25 years of research, consulting and teaching experience in UK, USA and India.
| Erscheinungsdatum | 24.05.2021 |
|---|---|
| Sprache | englisch |
| Maße | 178 x 254 mm |
| Gewicht | 633 g |
| Themenwelt | Informatik ► Theorie / Studium ► Algorithmen |
| Wirtschaft ► Betriebswirtschaft / Management ► Finanzierung | |
| ISBN-10 | 1-7998-4105-7 / 1799841057 |
| ISBN-13 | 978-1-7998-4105-0 / 9781799841050 |
| Zustand | Neuware |
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