Financial Modelling using Social Programming
نویسندگان
چکیده
This paper introduces Social Programming for use in predicting closing stock prices. Social Programming is a new methodology for creating Complex Adaptive Functional 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 Programming. The Social Programming algorithm was able to predict closing stock prices more effectively than the traditional Group Method of Data Handling. The results in this paper illustrate the potential of the Social Programming methodology for use in financial modelling.
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