Paper Title:
Intelligent Stock Trading Systems Using Fuzzy-Neural Networks and Evolutionary Programming Methods
  Abstract

The goal of this study was to analyze the possibilities of fuzzy neural networks and evolutionary programming methods for creating the human skill based stock trading systems. In stock exchange markets, the relationships between market variables are generally too complex to make rightful trading decisions and to earn stabile profits using classical system theory approach. On the other hand, there are a lot of trading experts-practicians that successfully trade stocks and achieve good results in the stock exchange markets. A useful technique for expert-knowledge extraction is the supervised learning methods, where human-experts actions are mapped using fuzzy-neural networks. In this paper we outline this procedure. Also we discuss the possibilities for improvement the proposed human skill based stock trading systems. An efficient biological system evolves slowly over the course of hundreds and housands of generations of individuals. Later generations have more fit and are more capable than earlier ones. Similarly, we have used evolutionary techniques to .evolve. the fuzzy-neural network based stock trading system, which is capable to solve the stock trading task more efficiently. Proposed procedure was tested using virtual trading system that uses historical data from US stock markets. The first results confirmed the good opportunities of the proposed approach.

  Info
Periodical
Solid State Phenomena (Volumes 97-98)
Edited by
Stepas Janušonis
Pages
59-64
DOI
10.4028/www.scientific.net/SSP.97-98.59
Citation
Rimvydas Simutis et al., 2004, Solid State Phenomena, 97-98, 59
Price
US$ 28,-
Share
Authors: Wang Lan Tian
Abstract:Fuzzy neural network, which can deal with complex data and prediction process that other algorithms can not accomplish, has become a focus in...
930
Authors: Zhao Hui Shi, Cheng Zhi Wang
Abstract:In this paper, we take characteristics of wastewater treatment and process technology, drawing on the effectiveness of thetraditional PID...
339
Authors: He Xiang Liu, Hai Tao Yu, Min Qiang Hu, Lei Huang, Li Yu
Chapter 1: Material Section
Abstract:In this paper, an acceleration compensating control approach is used for dealing with the non-linear dynamics of a multiple degrees of...
64
Authors: Xue Hui Yang, Xin Zhou
Chapter 17: Computer Applications in Industry and Civil Engineering
Abstract:The paper establishes the ship-bridge collision early warning model on the basis of Fuzzy Theory and neural network method, puts forward the...
2847
Authors: Pi Yun Chen, Yu Yi Fu, Kuo Lan Su, Jin Tsong Jeng
Chapter 7: Sensors, Mechatronics and Robotics
Abstract:In this paper, the Box–Cox transformation-based annealing robust fuzzy neural networks (ARFNNs) are proposed for identification of the...
2120