"This dissertation proposes the development of a hybrid intelligent system applied to technical analysis based equivolume charting for stock trading. A Neuro-Fuzzy based Genetic Algorithms (NF-GA) system of the Volume Adjusted Moving Average (VAMA) membership functions is introduced to evaluate the effectiveness of using a hybrid intelligent system that integrates neural networks, fuzzy logic, and genetic algorithms techniques for increasing the efficiency of technical analysis based equivolume charting for trading stocks"--Introduction, page 1.
Enke, David Lee, 1965-
Nystrom, Halvard E.
Grasman, Scott E. (Scott Erwin)
Dagli, Cihan H., 1949-
Engineering Management and Systems Engineering
Ph. D. in Engineering Management
University of Missouri--Rolla
Journal article titles appearing in thesis/dissertation
- Intelligent hybrid stock trading system for technical analysis based equivolume charting
- Intelligent technical analysis based equivolume charting for stock trading using neural networks
- Neruo-fuzzy volume adjusted moving averages for intelligent trading decisions
xi, 156 pages
© 2007 Thira Chavarnakul, All rights reserved.
Dissertation - Open Access
Library of Congress Subject Headings
Stock price forecasting -- Mathematical models
Stocks -- Charts, diagrams, etc. -- United States
Print OCLC #
Electronic OCLC #
Link to Catalog Recordhttp://laurel.lso.missouri.edu/record=b6148238~S5
Chavarnakul, Thira, "The development of hybrid intelligent systems for technical analysis based equivolume charting" (2007). Doctoral Dissertations. 1882.