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Evolutionary Money Management

  • Philip Saks
  • Dietmar Maringer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5484)

Abstract

This paper evolves trading strategies using genetic programming on high-frequency tick data of the USD/EUR exchange rate covering the calendar year 2006. This paper proposes a novel quad tree structure for trading system design.

The architecture consists of four trees each solving a separate task, but mutually dependent for overall performance. Specifically, the functions of the trees are related to initiating (“entry”) and terminating (“exit”) long and short positions. Thus, evaluation is contingent on the current market position. Using this architecture the paper investigates the effects of money management. Money management refers to certain measures that traders use to control risk and take profits, but it is found that it has a detrimental effects on performance.

Keywords

Exchange Rate Genetic Programming Trading Strategy Loss Aversion Foreign Exchange Market 
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-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Philip Saks
    • 1
  • Dietmar Maringer
    • 2
  1. 1.Centre for Computational Finance and Economic AgentsUniversity of EssexUK
  2. 2.Department for Quantitative Methods, Economics and Business FacultyUniversity of BaselSwitzerland

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