Double layer interval weighted graphs in assessing the market risks

This scientific work is dedicated to applying of two-layer interval weighted graphs in non-stationary time series forecasting and evaluation of market risks. The first layer of the graph, formed with the primary system training, displays potential system fluctuations at the time of system training. Interval vertexes of the second layer of the graph (the superstructure of the first layer) which display the degree of time series model-ing error are connected with the first layer by edges. The proposed model has been approved by the 90-day forecast of steel billets. The average forecast error amounts 2.6% (it's less than the average forecast error of the autoregression models).