Stock price prediction is a classic problem that has been analyzed by different tools and models. Stock market trend changes depends on supply and demand rule and other macroeconomic forces in the market circumstance. Non liner and full swing process makes it hard to pr More
Stock price prediction is a classic problem that has been analyzed by different tools and models. Stock market trend changes depends on supply and demand rule and other macroeconomic forces in the market circumstance. Non liner and full swing process makes it hard to predict future stock price. Traditional statistical techniques and models cannot explain seasonal and non-station time series data in stock markets. Hidden markov model has widely used in the way of predicting statistical time series. It extensively has used in such majors as speech recognition and DNA sequencing and also it can be used in order to next stock price prediction. In this study we tried to use discrete hidden markov model to predict next day’s index in Brussels (Euro Next) and answer the question that “which market will get the more accurate prediction by hidden markov model?.
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