Efficiency of Neural Networks in Forecasting Problems

Forecasting financial market trends is one of the most important tasks for investors. Traditional methods are complemented by machine learning methods, the potential of which is to find hidden knowledge in large amounts of information. Nonlinear models and methods based on artificial intelligence (neural networks) are considered. Currently, the real use of neural networks is developing in the following areas: stock exchange and macroeconomic forecasting; speech recognition and dialogue with the person; imitation of intellectual activity; improvement of poor-quality and noisy information; identification of suspicious persons and situations. In this paper it will be shown about the effective use of neural networks in forecasting problems.