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Trading Rule Generation for Foreign Exchange (FX)

  • Hitoshi Iba
  • Claus C. Aranha
Part of the Adaptation, Learning, and Optimization book series (ALO, volume 11)

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.

Keywords

Weight Vector Genetic Program Foreign Exchange Move Average Trading System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.School of Engineering, Dept. Information & Communication EngineeringUniversity of TokyoTokyoJapan
  2. 2.School of Frontier Sciences, Department of Frontier InformaticsThe University of TokyoTokyoJapan

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