Faculty Advisor

Becker, Lee A.

Abstract

Two artificial intelligence techniques, neural networks and genetic algorithms, are used for stock market prediction. Neural networks simulate the structure of the human brain and genetic algorithms simulate evolution through natural selection. Both algorithms take as input nine stock indicators and output a predicted rank for the stock. The performance of predicting with one model for each stock is compared with predicting all stocks with a single model.

Publisher

Worcester Polytechnic Institute

Date Accepted

January 2002

Major

Computer Science

Project Type

Major Qualifying Project

Accessibility

Restricted-WPI community only

Advisor Department

Computer Science

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