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Optimalizace nákupu a prodeje menoveho páru EUR/USD pomocí genetickych algoritmu jako klíc ke zvysování ziskovosti investicní strategie/Optimization of Buying and Selling Currency Pair EUR/USD with using of Genetic Algorithms as the Key to Increasing the Profitability of the Investment Strategy

Trendy ekonomiky a managementu, 2013-04, Vol.7 (15), p.18 [Peer Reviewed Journal]

Copyright Brno University of Technology, Faculty of Business and Management 2013 ;ISSN: 1802-8527 ;EISSN: 2336-6508

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  • Title:
    Optimalizace nákupu a prodeje menoveho páru EUR/USD pomocí genetickych algoritmu jako klíc ke zvysování ziskovosti investicní strategie/Optimization of Buying and Selling Currency Pair EUR/USD with using of Genetic Algorithms as the Key to Increasing the Profitability of the Investment Strategy
  • Author: Budík, Jan ; Smolíková, Lenka
  • Subjects: Currency transactions ; Investment policy ; Optimization algorithms ; Profit maximization ; Studies
  • Is Part Of: Trendy ekonomiky a managementu, 2013-04, Vol.7 (15), p.18
  • Description: The aim of this paper is to show the possibility of increasing the profitability of selected investment strategy, which is used for trading currency pair EUR/USD. Model strategy is based on the assumption of continuing the trend yesterday, and only works with the days when the price rose. Due to the computationally intensive tasks genetic algorithms are used to significantly reduce the time for finding the optimal values of selected parameters. The study of the currency pair EUR/USD is done using technical analysis. To enter investment position, the method is based on the momentum of price movements and its subsequent sequels. The scientific contribution of this paper is the implementation of genetic algorithms in the process of increasing the profitability of investment strategies. The analysis and optimization found optimal parameter values for the modification of the original strategy. These parameters include the precise timing of input in terms of hours.
  • Publisher: Brno: Brno University of Technology, Faculty of Business and Management
  • Language: English;German
  • Identifier: ISSN: 1802-8527
    EISSN: 2336-6508
  • Source: ProQuest Central
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