A smart agent to trade and predict foreign exchange market

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@InProceedings{Alrefaie:2013:CIES,

• author = "Mohamed Taher Alrefaie and Alaa-Aldine Hamouda and Rabie Ramadan",
• booktitle = "IEEE Symposium on Computational Intelligence for Engineering Solutions (CIES 2013)",
• title = "A smart agent to trade and predict foreign exchange market",
• year = "2013",
• month = apr,
• pages = "141--148",
• keywords = "genetic algorithms, genetic programming, foreign exchange trading, probability, US dollars daily turnover, adaptive neuro-fuzzy inference system, foreign exchange market, genetic programming approach, probability, smart agent, Companies, Fluctuations, Market research, Prediction algorithms, Predictive models, Profitability, ANFI, Agent, Forex, NSGA-II, Prediction",
• DOI = "doi:10.1109/CIES.2013.6611741",
• size = "8 pages",
• abstract = "Foreign Exchange market is a worldwide market to exchange currencies with 3.98 trillion US dollars daily turnover. With such a massive turnover, probability of profit is very high; however, trading in such massive market needs high knowledge, skills and full commitment in order to achieve high profit. The purpose of this work is to design a smart agent that 1) acquire Foreign Exchange market prices, 2) pre-processes it, 3) predicts future trend using Genetic Programming approach and Adaptive Neuro-fuzzy Inference System and 4) makes a buy/sell decision to maximise profitability with no human supervision.",
• notes = "Also known as \cite{6611741}",

}

Genetic Programming entries for Mohamed Taher Alrefaie Alaa-Aldine Hamouda Rabie Ramadan

Citations