Forecasting the Stock Market with ANNs and Autonomous Agents

Abstract

Investment strategies usually aim at achieving maximum profitability what, according to current management theory (Refenes, Burgess, & Bentz, 1997), can be obtained by the construction of well balanced investment portfolios that seek to maximum return and minimum risks. In order to provide users with information to plan a good investment portfolio, we present an e-commerce Web site solution that enables users to estimate in advance investments return and risks. The application, which is based on computational intelligence techniques, aims at forecasting and divulging the share prices of the main companies listed in the stock market. Artificial neural networks (ANNs) (Haykin, 1999) that have been used successfully in many other financial time series applications (Braga, Carvalho, Lurdemir, Almeida, & Lacerda, 2002; Refenes, et al., 1997; Zhang, 2003) were used as the main forecasting engine of the system. Autonomous agents (Paolucci, Sycara, & Kawamura, 2003; Russel & Norvig, 1995) are responsible for collecting, on a daily basis, information regarding sale and purchase of shares. The information collected is then used by the ANN to forecast future stock market trends and closing values. The Web site offers free of charge services, such as access to forecasting charts, simulation of investments and general guidelines for buying and selling shares.