IMPROVED PREDICTING NICKEL PRICE BY AVERAGING RESULTS OF PREDICTED VALUES

The paper focuses on the fact that Russia is one of the main exporters of ferrous and non-ferrous metals on the world market. A large sector of producers and traders with this raw material is represented in the country. For successful trading it is necessary to know the prices in the future, when the contract is concluded for the export delivery of a consignment of goods, the parties often fix the price at the time of signing the treaty. By the time of cargo shipment the price may suddenly change, so that the transaction would be disadvantageous for the exporter. Today, companies are actively using forecasting and, in the case of the global market, they are guided by global stock quotes. The prices on base metals correlate well with each other, for simplicity, and forecasting nickel price quotes is more available to take as an example. It has been stated that from the time of making the contract to the time of delivery there pass 14 days, which requires forecasting 14 steps ahead (long warning period). This fact causes the main difficulty in achieving the required accuracy. The prediction accuracy is suggested by using simple and weighted averaging of the predicted values of several models. The results of using several models of common statistical forecasting and developed in the course of the research are presented. The mean forecasting error of nickel price quotations for the period from March, 2015 to March, 2016 for 14 days ahead for the best of the given values made 6.48%, for the worst value - 14.88%. The simple averaging value has shown a prediction error of 6.01%, and the weighted value - 3.58%. It has been inferred that using this technique improves the accuracy of the available forecasting models in practice.