Method of training neural networks for use in exchange robots based on intuitive analysis

Abstract

The article deals with the development of teaching methodology for exchange robots based on neural networks using intuitive analysis for more effective evaluation of the securities. The article compares methods, which used by the human brain during assessment and finding solutions for tasks, with the algorithms, which used in modern exchange stock robots, in order to develop new and innovative algorithms to improve the efficiency of trading robots that take advantage of the intuitive analysis. The article gives the necessity to use non-standard methods of analysis such as intuition, and provides suggestions for its implementation in the algorithms used in trade robots.

Keywords

• market securities
• securities
• neural networks
• perceptron
• intuition