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Workshops on Applications of Evolutionary Computation

EvoWorkshops 2009: Applications of Evolutionary Computing pp 162–171Cite as

Evolutionary Money Management

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,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.

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References

  1. Allen, H., Taylor, M.P.: Charts, noise and fundamentals in the London foreign exchange market. The Economic Journal 100(400), 49–59 (1990)

    Article  Google Scholar 

  2. Bhattacharyya, S., Pictet, O.V., Zumbach, G.: Knowledge-intensive genetic discovery in foreign exchange markets. IEEE Transactions on Evolutionary Computation 6(2), 169–181 (2002)

    Article  Google Scholar 

  3. Chang, K., Osler, C.L.: Methodical madness: Technical analysis and the irrationality of exchange-rate forecasts. The Economic Journal 109, 636–661 (1999)

    Article  Google Scholar 

  4. Dacorogna, M.M., Gencay, R., Müller, U.A., Olsen, R.B., Pictet, O.V.: An Introduction to High-Frequency Finance. Academic Press, London (2001)

    Google Scholar 

  5. Dempster, M.A.H., Jones, C.M.: A real-time adaptive trading system using genetic programming. Quantitative Finance 1, 397–413 (2001)

    Article  Google Scholar 

  6. Fama, E.F.: Efficient capital markets: A review of theory and empirical work. Journal of Finance 25(2), 383–417 (1970)

    Article  Google Scholar 

  7. Jonsson, H., Madjidi, P., Nordahl, M.G.: Evolution of trading rules for the FX market or how to make money out of GP, Technical report, Institute of Theoretical Physics, Chalmers University of Technology (1997)

    Google Scholar 

  8. Kahneman, D., Tversky, A.: Prospect theory: An analysis of decision under risk. Econometrica 47(2), 263–291 (1979)

    Article  MATH  Google Scholar 

  9. LeBaron, B.: Technical trading profitability in foreign exchange markets in the 1990’s, Technical report, Brandeis University (2002)

    Google Scholar 

  10. Maillet, B., Michel, T.: Further insights on the puzzle of technical analysis profitability. The European Journal of Finance 6, 196–224 (2000)

    Article  Google Scholar 

  11. Meese, R., Rogoff, K.: Empirical exchange rate models of the seventies, do they fit out-of-sample? Journal of International Economics 14, 3–24 (1983)

    Article  Google Scholar 

  12. Menkhoff, L., Taylor, M.P.: The obstinate of foreign exchange professionals: Technical analysis (2006)

    Google Scholar 

  13. Neely, C.J., Weller, P.A.: Intraday technical trading in the foreign exchange market, Technical report, Federal Reserve Bank of St Louis (1999)

    Google Scholar 

  14. Osler, C.L.: Currency orders and exchange rate dynamics: An explanation for the predictive success of technical analysis. The Journal of Finance 58(5), 1791–1819 (2003)

    Article  Google Scholar 

  15. Saks, P., Maringer, D.: Evolutionary money management, Technical report, Centre for Computational Finance and Economic Agents, University of Essex (2008)

    Google Scholar 

  16. Saks, P., Maringer, D.: Genetic programming in statistical arbitrage. In: Giacobini, M., Brabazon, A., Cagnoni, S., Di Caro, G.A., Drechsler, R., Ekárt, A., Esparcia-Alcázar, A.I., Farooq, M., Fink, A., McCormack, J., O’Neill, M., Romero, J., Rothlauf, F., Squillero, G., Uyar, A.Ş., Yang, S. (eds.) EvoWorkshops 2008. LNCS, vol. 4974, pp. 73–82. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  17. Thaler, R., Tversky, A., Kahneman, D., Schwartz, A.: The effect of myopia and loss aversion on risk taking: An experimental test. The Quarterly Journal of Economics 112(2), 647–661 (1997)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Centre for Computational Finance and Economic Agents, University of Essex, UK

    Philip Saks

  2. Department for Quantitative Methods, Economics and Business Faculty, University of Basel, Switzerland

    Dietmar Maringer

Authors
  1. Philip Saks
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  2. Dietmar Maringer
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Editor information

Editors and Affiliations

  1. Department of Animal Production Epidemiology and Ecology, University of Torino, Via Leonardo da Vinci 44, 10095, Grugliasco, Italy

    Mario Giacobini

  2. Quinn School of Business, Belfield, University College Dublin, Dublin 4, Ireland

    Anthony Brabazon

  3. Department of Computer Engineering, University of Parma, Viale Usberti 181/a, 43100, Parma, Italy

    Stefano Cagnoni

  4. Dalla Molle Institute for Artificial Intelligence (IDSIA), Gallelria 2, 6928, Manno-Lugano, Switzerland

    Gianni A. Di Caro

  5. School of Engineering and Applied Science,Aston Triangle, Aston University, B4 7ET, Birmingham, UK

    Anikó Ekárt

  6. Complex Adaptive Systems Group, Instituto Tecnológico de Informática, Ciudad PolitŽcnica de la Innovacin, Edif. 8G Acceso B, 46022, Valencia, Spain

    Anna Isabel Esparcia-Alcázar

  7. Next Generation Itelligent Networks Research Center (nexGIN RC), National University of Computer and Emerging Sciences (NUCES), Islamabad, Pakistan

    Muddassar Farooq

  8. Faculty of Economics and Social Sciences, Helmut-Schmidt-University, Holstenhofweg 85, 22043, Hamburg, Germany

    Andreas Fink

  9. Department of Informatics Engineering, Polo II - Pinhal de Marrocos, University of Coimbra, 3030 - 290, Coimbra, Portugal

    Penousal Machado

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© 2009 Springer-Verlag Berlin Heidelberg

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Saks, P., Maringer, D. (2009). Evolutionary Money Management. In: Giacobini, M., et al. Applications of Evolutionary Computing. EvoWorkshops 2009. Lecture Notes in Computer Science, vol 5484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01129-0_20

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  • DOI: https://doi.org/10.1007/978-3-642-01129-0_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01128-3

  • Online ISBN: 978-3-642-01129-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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