A Hybrid Neural Network System for Trading Financial Markets

  • Marina Resta
Part of the Springer Finance book series (FINANCE)


In this chapter Marina Resta demonstrates experimentally the great potential of neural networks for design of systems for trading stock markets. She suggests the use of a hybrid neural network architecture that combines the approach of Self-Organizing Maps together with that of Genetic Algorithms. She shows the forecasting capabilities of this hybrid system and evidence of the performance of this system. This chapter is a nice extension of the applications of trading systems presented in “Trading on the Edge”. The novelty here is that genetic algorithms and self-organizing maps are combined.


Financial Market Arbitrage Opportunity Daily Fluctuation Random Decision Hybrid Neural Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Marina Resta

There are no affiliations available

Personalised recommendations