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Forecasting exchange rate is very important for many international agents e.g. investors, money managers, investment banks, funds makers and others. We forecasted the daily Bangladeshi exchange rate series for the period of January 1992 to March 2009 using popular non-linear forecasting models, namely Markov switching autoregressive model, fuzzy extension of artificial neural network model (ANFIS)...
This paper presents rough sets generating prediction rules scheme for stock price movement. The scheme was able to extract knowledge in the form of rules from daily stock movements. These rules then could be used to guide investors whether to buy, sell or hold a stock. To increase the efficiency of the prediction process, rough sets with Boolean reasoning discretization algorithm is used to discretize...
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