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Genetic algorithm for arbitrage with more than three currencies

Author

Listed:
  • Adrián Fernández-Pérez

    (Universidad de Las Palmas de Gran Canaria)

  • Fernando Fernández-Rodríguez

    (Universidad de Las Palmas de Gran Canaria)

  • Simón Sosvilla-Rivero

    (Universidad Complutense de Madrid)

Abstract

We develop a genetic algorithm that is able to find the optimal sequence of exchange rates that maximizes arbitrage profits with more than three currencies, being both the triangular arbitrage and the direct exchange rate two special cases of the proposed algorithm. Applying the algorithm to the most traded currencies, we find average profits ranking from 4.5083% to 0.3162% for changing 1 USD for EUR with respect to the direct exchange rate, for different transaction costs, during the period October 2000- April 2012. Our results also suggest that the arbitrage profits increased just after the subprime crisis in summer of 2007 and that they are higher when the market is less liquid.

Suggested Citation

  • Adrián Fernández-Pérez & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, 2012. "Genetic algorithm for arbitrage with more than three currencies," Working Papers 12-04, Asociación Española de Economía y Finanzas Internacionales.
    • Handle: RePEc:aee:wpaper:1204
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    References listed on IDEAS

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    1. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    2. Grossman, Sanford J & Stiglitz, Joseph E, 1976. "Information and Competitive Price Systems," American Economic Review, American Economic Association, vol. 66(2), pages 246-253, May.
    3. Alan Carruth & Andy Dickerson & Andrew Henley, 2000. "What do We Know About Investment Under Uncertainty?," Journal of Economic Surveys, Wiley Blackwell, vol. 14(2), pages 119-154, April.
    4. Pastor, Lubos & Stambaugh, Robert F., 2003. "Liquidity Risk and Expected Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 111(3), pages 642-685, June.
    5. repec:bla:jecsur:v:14:y:2000:i:2:p:119-53 is not listed on IDEAS
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    Cited by:

    1. Jacinta Chan Phooi M'ng & Azmin Azliza Aziz, 2016. "Using Neural Networks to Enhance Technical Trading Rule Returns: A Case with KLCI," Athens Journal of Business & Economics, Athens Institute for Education and Research (ATINER), vol. 2(1), pages 63-70, January.

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    More about this item

    Keywords

    Arbitrage; Foreign Exchange Market; Genetic Algorithm;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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