Development and investigation of the methods for adaptive forecasting and statistical identification based on non-linear dynamic models of physical and economic processes
The method of GARCH model synthesis (Generalized autoregressive conditional heteroscedasticity) was developed for prediction of maximal sample conditional variances of output coordinates of multidimensional heteroscedastic processes with multirate discretization. To achieve maximal prediction accuracy the algorithm of adaptive adjustment of GARCH model coefficients was devised.