Abstract
This paper contributes an application of Cartesian Genetic Programming Evolved Artificial Neural Network (CGPANN) for forecasting the foreign currency exchange rates. The end product of our work is an efficient Artificial Neural Network (ANN) based prediction model that forecasts the foreign currency exchange rates, making use of the trends in historical data. These trends in the historical currency data serve as significant prognostic factor to train the prediction model. The algorithm exploited for the evolution of the prediction model is Cartesian Genetic Programming (CGP). CGP evolved ANNs have great potential in prediction models for forecasting systems. Historical daily prices of 500 days data of US dollars are monitored to train the prediction model. Once the model is trained, it is tested on 1000 days data of ten different currencies to predict these currency rates and the results are monitored to analyze the efficiency of the system. The results show that prediction model achieved with CGPANN is computationally cost effective and accurate (98.85%) that is unique as it is dependent on least amount of previous data for future data prediction.
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References
Philip, A.A., Tofiki, A.A., Bidemi, A.A.: Artificial Neural Network Model for Forecasting Foreign Exchange Rate. World of Computer Science and Information Technology Journal 1(3), 110–118 (2011)
Gould, J.H.: Forex Prediction Using An Artificial Intelligent System. Diss., Oklahoma State University (2004)
Zhang, G., Hu, M.Y.: Neural Network Forecasting of the British Pound/ US Dollar Exchange Rate. Omega, Int. J. Mgmt. Sci. 26(4), 495–506 (1998)
Kryuchin, O.V., Arzamastsev, A.A., Troitzsch, K.G.: The prediction of currency exchange rates using artificial neural networks. Exchange Organizational Behavior Teaching Journal (4) (2011)
Refenes, A.N., Azema-Barac, M., Chen, L., Karoussos, S.A.: Currency Exchange Rate Prediction and Neural Network Design Strategies. Neural Computing & Applications 1(1), 46–58 (1993)
Kadilar, C., Alada, H.: Forecasting the Exchange Rate Series with ANN: The case of Turkey. Economics and Statistics Changes 9, 17–29 (2011)
Khan, G.M., Khan, S., Ullah, F.: Short-term daily peak load forecasting using fast learning neural network. In: IEEE Int. 11th International Conference on Intelligent Systems Design and Applications, ISDA (2011)
Kamruzzaman, J., Sarker, R.A.: Forecasting of Currency Exchange Rates Using ANN: A Case Study. In: Proceedings of the IEEE International Conference on Neural Networks & Signal Processing, vol. 1, pp. 793–797 (2003)
Poli, R.: Parallel Distributed Genetic Programming Applied to the Evolution of Natural Language Recognisers. Evolutionary Computing, 163–177 (1997)
Bidlo, M.: Evolutionary Design of Generic Combinational Multipliers Using Development. In: Kang, L., Liu, Y., Zeng, S. (eds.) ICES 2007. LNCS, vol. 4684, pp. 77–88. Springer, Heidelberg (2007)
Haider, A., Hanif, M.N.: Inflation Forecasting in Pakistan using Artificial Neural Networks. Pakistan Economic and Social Review 47, 123–138 (2009)
Jeng, J.T., Tain, L.T.: An approximate equivalence neural network to conventional neural network for the worst-case identification and control of nonlinear system. In: IEEE International Joint Conference on Neural Networks, IJCNN, vol. 3, pp. 2104–2108 (1999)
Miller, J.F., Thomson, P.: Cartesian Genetic Programming. In: Poli, R., Banzhaf, W., Langdon, W.B., Miller, J., Nordin, P., Fogarty, T.C. (eds.) EuroGP 2000. LNCS, vol. 1802, pp. 121–132. Springer, Heidelberg (2000)
Floreano, D., Durr, P., Mattiussi, C.: Neuroevolution: from architectures to learning. Evolutionary Intelligence 01, 47–62 (2008)
Gomes, F., Schmidhuber, J.: Accelerated Neural Evolution through Cooperatively Coevolved Synapses. Journal of Machine Learning Research 9, 937–965 (2008)
Atiya, A.F., E1-shoura, S.M., Shaheen, S.I., El-Sherif, M.S.: A Comparison between Neural-Network Forecasting Techniques- Case Study: River Flow Forecasting. IEEE Transactions on Neural Networks 10(2), 402–409 (1999)
Chen, A.P., Hsu, Y.C., Hu, K.F.: A Hybrid Forecasting Model for Foreign Exchange Rate Based on a Multi-neural Network. In: IEEE Fourth International Conference on. Natural Computation, ICNC 2008, pp. 293–298 (2008)
Azoff, E.M.: Neural network time series forecasting of financial markets. John Wiley and Sons Inc., Chichester (1994)
Pacelli, V., Bavelacqua, V., Azzollini, M.: An Artificial Neural Network Model to Forecast Exchange Rates. Journal of Intelligent Learning Systems and Applications 3(2), 57–69 (2011)
Igel, C.: Neuroevolution for reinforcement learning using evolution strategies. In: The 2003 Congress on Evolutionary Computation, CEC 2003, vol. 4. IEEE (2003)
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Nayab, D., Muhammad Khan, G., Mahmud, S.A. (2013). Prediction of Foreign Currency Exchange Rates Using CGPANN. In: Iliadis, L., Papadopoulos, H., Jayne, C. (eds) Engineering Applications of Neural Networks. EANN 2013. Communications in Computer and Information Science, vol 383. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41013-0_10
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DOI: https://doi.org/10.1007/978-3-642-41013-0_10
Publisher Name: Springer, Berlin, Heidelberg
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