Artificial Neural Network (ANN), Min-Max Normalization, Iterative Approach, Stock Price Predication
Predicting stock price of a particular stock is a difficult non-linear problem. Artificial Neural Network (ANN) is a tool to solve this kind of problem and has received much attentions in the field of financial modeling in recent years. This paper proposes an enhanced ANN for predicting stock prices with a novel Max-Min normalization method as well as an iterative approach. Our experimental results confirm that the predication accuracy outperforms other existing ANN predication mechanisms.
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