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