Adapted methods of nonlinear dynamics for preparation of economical time series data to forecasting procedure

  • Альфира Менлигуловна Кумратова Kuban State Agrarian University
  • Елена Витальевна Попова Kuban State Agrarian University
  • Светлана Ивановна Турлий Kuban State Agrarian University
  • Татьяна Алексеевна Недогонова Kuban State Agrarian University
Keywords: complex analysis, time series, nonlinear trend, linear trend, visualization, Gilmore test, pseudo-phase space, attractor

Abstract

Purpose: аuthors propose to use adapted methods of nonlinear dynamics for preparation of economical time series data to forecasting procedure in order to identify chaotic dynamics and choose forecasting methods and models. Discussion: each step of the proposed set of methods for preliminary data processing allows us to put forward proposals on certain properties of the time series under study. This, in turn, proves that in order to obtain reliable and reasonable conclusions about the type of behavior of the system under study, there are not enough results from one of the many existing tests. Results: сonducting a comprehensive analysis will make it possible to most correctly determine the behavior type of the time series and its characteristics, which will make it possible to obtain a further reliable forecast.

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Published
2019-08-20
How to Cite
Кумратова, А. М., Попова, Е. В., Турлий, С. И., & Недогонова, Т. А. (2019). Adapted methods of nonlinear dynamics for preparation of economical time series data to forecasting procedure. Modern Economics: Problems and Solutions, 7, 33-41. https://doi.org/10.17308/meps.2019.7/2155
Section
Mathematical Methods in Economics