Faculty Advisor

Becker, Lee A.

Faculty Advisor

Ruiz, Carolina

Abstract

We propose and investigate a novel cooperative co-evolutionary framework that evolves genetic algorithms in parallel to predict the performance of the stock market. We introduce several alternate methods to decompose the prediction problem, including a recursive specialization scheme, and conduct extensive experimentation to compare them. Experimental results revealed a tradeoff between classification accuracy and precision as a result of a tradeoff between specialization and generalization of the co-evolutionary scheme.

Publisher

Worcester Polytechnic Institute

Date Accepted

January 2004

Major

Computer Science

Project Type

Major Qualifying Project

Accessibility

Restricted-WPI community only

Advisor Department

Computer Science

Advisor Program

Computer Science

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