Title :
A smart agent to trade and predict foreign exchange market
Author :
Alrefaie, Mohamed T. ; Hamouda, Alaa-Aldine ; Ramadan, Rido
Author_Institution :
Syst. & Comput. Eng. Dept., Al-Azhar Univ., Cairo, Egypt
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 maximize profitability with no human supervision.
Keywords :
foreign exchange trading; genetic algorithms; probability; US dollars daily turnover; adaptive neuro-fuzzy inference system; foreign exchange market; genetic programming approach; probability; smart agent; Companies; Fluctuations; Genetic algorithms; Market research; Prediction algorithms; Predictive models; Profitability; ANFI; Agent; Forex; Genetic Algorithm; NSGA-II; Prediction;
Conference_Titel :
Computational Intelligence for Engineering Solutions (CIES), 2013 IEEE Symposium on
Conference_Location :
Singapore
DOI :
10.1109/CIES.2013.6611741
