Abstract
This paper describes a method to reduce the uncertainty about investments in stock market. The objective is to predict the movements of the Bovespa Stock Index through multiagent system. The proposed system has a population of agents for each asset that is a constituent part of the stock index. Agents have learning skills due to the use of neural networks. Predict the direction of the populations of agents is more efficient than predict the direction based only on data in the index time series.
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Antonello, R., Silveira, R.A. (2010). Multiagent Systems in Stock Index Prediction. In: Demazeau, Y., et al. Trends in Practical Applications of Agents and Multiagent Systems. Advances in Intelligent and Soft Computing, vol 71. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12433-4_66
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DOI: https://doi.org/10.1007/978-3-642-12433-4_66
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12432-7
Online ISBN: 978-3-642-12433-4
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