Financial Modelling using Social Programming

M.S. Voss and J.C. Howland III (USA)


Social Programming, Genetic Programming, ParticleSwarm Optimization, GMDH, Stock Prediction


This paper introduces Social Programming for use in predicting closing stock prices. Social Programming is a new methodology for creating Complex Adaptive Func tional Networks that is based on a social-psychological metaphor. Social Programming is demonstrated to be a logical extension of the Particle Swarm methodology, the Group Method of Data Handling and Cartesian Program ming. The Social Programming algorithm was able to pre dict closing stock prices more effectively than the tradi tional Group Method of Data Handling. The results in this paper illustrate the potential of the Social Programming methodology for use in financial modelling.

Important Links:

Go Back