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This paper is a survey on the application of artificial neural networks in forecasting financial market prices. The objective of this paper is to appraise the potential of using artificial neural networks to predict the financial system, as it is reflected in many relevant articles. It will provide some guidelines and references for the research and implementation. This paper begins with an introduction to the theory of artificial neural networks. Subsequently it focuses on the forecast of stock prices and option pricing based on a non-linear ANN model. It proceeded with a presentation of the application of ANN in predicting exchange rates. The paper then reviewed the theoretical literature on the prediction of banking and financial crisis based on artificial neural networks. In general artificial neural network is a valuable forecast tool in financial economics due to the learning, generalization and nonlinear behavior properties. Finally it identifies a number of important opportunities for future research on the application of neural networks in financial economics.
Li et al. (Fri,) studied this question.