期刊名称：Journal of Advanced Computer Science & Technology
印刷版ISSN：2227-4332
电子版ISSN：2227-4332
出版年度：2015
卷号：4
期号：1
页码：84-89
DOI：10.14419/jacst.v4i1.4194
出版社：Science Publishing Corporation
摘要：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.
