On the properties of non-linearity of dynamic socio-economic systems and processes

Abstract

Purpose: this article is devoted to the use of instrumental and mathematical methods for modeling time series of personal and social insurance based on fractal analysis. Discussion: the methods of fractal analysis used and adapted by the author provide identification and evaluation of a number of fundamental characteristics of socio-economic time series, namely, such pre-forecast characteristics as memory depth, persistence or anti- persistence, trend stability or reversal of more often random, color noise. Results: the study allowed us to adapt and offer a complete system of models and methods for fractal analysis of time series to ensure greater reliability of subsequent forecasting.