Title :
Technical data analysis for movement prediction of Euro to USD using Genetic Algorithm-Neural Network
Author :
Sespajayadi, Ary ; Indrabayu ; Nurtanio, Ingrid
Author_Institution :
Artificial Intell. & Multimedia Process. Res. Group, Hasanuddin Univ., Makassar, Indonesia
Abstract :
In the foreign currency exchange (FOREX), a technical data analysis system for predicting currency movements is needed to help traders in decision making. Thus, this study proposes a system of technical data analysis to movement prediction of Euro to USD using Genetic Algorithm-Neural Network (GANN). To generate a predicted value, Genetic Algorithm searching for the best value of Feed Forward Neural Network (FFNN) trained with the Neural Network method that produced a net to predict. The Validation of predicted results with GANN method based on the degree of accuracy as follows. RMSE values of open is 0.00043; The RMSE values of high is 0.00068; The RMSE value of low is 0.00075; and RMSE values of close is 0.00070.
Keywords :
data analysis; decision making; feedforward neural nets; foreign exchange trading; genetic algorithms; Euro; FFNN; GANN method; USD; currency movement prediction; decision making; feed forward neural network; foreign currency exchange; forex; genetic algorithm-neural network; technical data analysis system; Accuracy; Artificial neural networks; Biological cells; Genetic algorithms; Prediction algorithms; Training; forex; gann; genetic algorithm; neural network; prediction;
Conference_Titel :
Intelligent Technology and Its Applications (ISITIA), 2015 International Seminar on
Conference_Location :
Surabaya
Print_ISBN :
978-1-4799-7710-9
DOI :
10.1109/ISITIA.2015.7219947