Abstract
In the previous chapters we described how we can use Evolutionary Computation to perform forecasting in financial data and trend analysis. In both cases, computational intelligence, in the form of EC, processes large amounts of financial data, and transforms it into information that can be used by a human trader.
But what if we want to design a computational agent that is able to perform trades from end to end? The artificial trader would be able to receive raw technical data, such as the price of stocks or exchange rates, and analyze it. Based on the information from this analysis, it can autonomously make a trading decision, such as buying or selling.
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© 2012 Springer Berlin Heidelberg
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Iba, H., Aranha, C.C. (2012). Trading Rule Generation for Foreign Exchange (FX). In: Practical Applications of Evolutionary Computation to Financial Engineering. Adaptation, Learning, and Optimization, vol 11. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27648-4_6
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DOI: https://doi.org/10.1007/978-3-642-27648-4_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27647-7
Online ISBN: 978-3-642-27648-4
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