%0 Journal Article
%T Forecasting about EURJPY exchange rate using hidden Markova model and CART classification algorithm
%A Abdorrahman Haeri
%A Kamran Rezaie
%A Seyed Morteza Hatefi
%J -
%D 2015
%R 10.14419/jacst.v4i1.4194
%X The goal of this paper is forecasting direction (increase or decrease) of EURJPY exchange rate in a day. For this purpose five major indicators are used. The indicators are exponential moving average (EMA), stochastic oscillator (KD), moving average convergence divergence (MACD), relative strength index (RSI) and Williams %R (WMS %R). 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 rates in a day. Also the approach is used for forecasting differnece between intial and maximum exchange rates in a day. As well as it is used for forecasting differnece between intial and minimum exchange rates in a day. Reslut of proposed method is compared with CART and neural network. Comparison shows that the forecasting with proposed method has higher accuracy.
%U https://www.sciencepubco.com/index.php/JACST/article/view/4194