FORECASTING THE BEHAVIOR OF EXCHANGE FUTURES MARKET OF AGRICULTURAL PRODUCTS

Анотація

Introduction. This article presents the analysis of the methodology for forecasting the behavior of the market based on the analysis of the market for financial contracts, giving the opportunity to see the basic idea of the forecast methodology of the market in the process of calculating the forecast values of the market behavior prognosis. The purpose of the article is to study the risks and forecasts for the behavior of the exchange futures market for agricultural products. Results. It is evident that the methodology for forecasting the behavior of the market based on analyzing the standard of futures contracts for wheat has been gradually receiving new information and until the end of the period reflects the main trends. The behavior of a particular point is also analyzed, but when the horizontal trend of the coordinate of a particular point is the same, when moving to the input trend, the coordinates of a particular point are seen from a particular point and the trend towards a particular coordinate is shown in line with the horizontal trend, and the difference between the coordinates and the real values of the price is positive. Carrying out a test of the other methods for forecasting economic indicators with the help of the advancement of the additional Brown model and the A-Y-model, implemented in the package of engineering projects of MatLаb, helps define the contract price. That is, when forecasting the dynamics of the markets of futures contracts, as a rule, the dynamics of the forecasting methods will change dramatically. Further, the urgency of the problem of investment and forecasting of market tends is not only due to the interests of private or corporate investors. Adequate information about the development of the market is necessary for securing the needs of the state administration bodies. Conclusions. The comparison of different methods of forecasting economic indicators with the proposed approach was made. It is highlighted that a Brown model and a standard neural network, implemented in the MatLab engineering calculation package specifically for forecasting asset dynamics, were chosen for this study. Keywords: futures, futures market, agricultural products, forecasting, risks, exchange, stock market.

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