PREDICTING STOCK MARKET BEHAVIOR USING NEURAL NETWORKS

Abstract

With the recent boom in the world, especially in the technology aspect, the financial world has begun to use methods and means that help the investor achieve the highest returns with little risk. One of these methods is the use of neural network matrices as a starting point for building models for predicting the movement of stock prices in the stock market for the purpose of working to predict what might be in the future regarding stock prices. The research dealt with the multi-layer neural network model in the statement of inputs, outputs and the hidden layer. The results showed that this model has a high accuracy in predicting stock prices in the future, due to the features it carries that help the investor in making an investment decision. However, what is taken on the model is that it is characterized by complexity and the need to work on it by a specialist and not an ordinary investor. The research put forward a set of recommendations, the most important of which was working to raise the level of learning among the investor in order to benefit from these capabilities in using multiple methods in building his investment path.