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Abstract

The article describes the methods and models of prediction in the case of the stock market. There are different methods for assessing and predicting in the case of the stock market, which are widely used in practice in the present. In this paper, we used the model of Moving Average Convergence/ Divergence, prediction model based on a neural network, model of autoregressive integrated moving average (ARIMA) for prediction. We identified the conditions of the use the models as indicators in the case of the market, show examples of application models on the data of the closing prices for the exchange rate from dollar USD to ruble in Russia. In this article analyzes the disadvantages of these models and the causes of these deficiencies. The materials characteristics in this article are analyzing the practical orientation of prediction models in the case of the stock market and interpret the results of mistaken prediction.