Optimalizace nákupu a prodeje měnového páru EUR/USD pomocí genetických algoritmů jako klíč ke zvyšování ziskovosti investiční strategie - Budík, Jan; Smolíková, Lenka (Vysoké učení technické v Brně, Fakulta podnikatelská, 2013)
Purpose of the article: 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. In the event that the trend of rising yesterday’s, so at the beginning of the current buy is made and the current at the end of the sell is made. In the long term this investment strategy unprofitable. The research in this paper works with possibilities placement optimization buy order to the market so that long-term strategy was profitable. Due to the computationally intensive tasks are used genetic algorithms to significantly reduce the time for finding the optimal values of selected parameters. Methodology/methods: Method study the currency pair EUR/USD is done using technical analysis. To enter investment position, the method based on the momentum of price movements and its subsequent sequels. The original proposal of a long-term strategy is not profitable and increase profitability using methods strategy is modified into a form that generates a long-term gain. Scientific aim: Scientific contribution of this paper is the implementation of genetic algorithms in the process of increasing the profitability of investment strategies. This is achieved by adding an additional parameter to specify entry into investment position. Findings: The analysis and optimization were found optimal parameter values for the modification of the original strategy. These parameters include the precise timing of input in terms of hours, as well as making a buy at a discounted price using the LIMIT order. Due to the implementation of financial leverage is necessary to secure positions with automatic order to exit positions at a loss. Selection of positions with a higher probability of profit is secured by a rule that allows the current trading day only yesterday when he was big enough difference between the opening and closing price. Conclusions: Modified strategy is used in the simulation to account for the size of $ 50.000. During the period from 1. 1. 2009 to 31. 12. 2012 evaluate the account to $ 67.722, an increase of 35,45%.
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
Keywords: Optimization; genetic algorithm; technical analysis; investment strategies; currency