Abstract
From numerous approaches studying the prediction of stock price, this paper proposed a new approach which was the combination of RBF neural network and Markov chain to forecast the stock closing price of the Shanghai composite index. Markov chain was aimed at making the error between the actual price and predicted price obtained by RBF neural network correct. Besides, for higher prediction accuracy, genetic algorithm was used to optimize the state division of Markov chain. The experimental result confirmed its effectiveness and superiority in comparison with the other two methods in some time interval.
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