Abdorrahman Haeri - Department of Industrial engineering, University College of engineering, University of Tehran, Iran
Fariborz Jolai - Department of Industrial engineering, University College of engineering, University of Tehran, Iran

The goal of this paper is forecasting the direction (increase or decrease) of EURJPY exchange rate in a day. For this purpose five major indicators are used. Then a hybrid approach using hidden Markov models and CART classification algorithms is developed. Proposed approach is used for forecasting direcation (increase or decrease) of Euro-Yen exchange rate in a day. Also the approach is used for forecasting differnece between intial and maximum (minimum) exchange rates in a day. Result of proposed method is compared with CART and neural network. Comparison shows that the forecasting with proposed method has higher accuracy.

foreign exchange market, forecasting, CART classification algorithm, hidden Markov model, EURJPY exchange rate