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Risks assessment and forecasting long time rows of economic indicators

Author

Listed:
  • Gennadiy Bystray
  • Ivan Lykov

    (Ural Federal University named after the first President of Russia B. N. Yeltsin)

  • Natalya Nikulina

    (Institute of Economics of the Ural Branch of Russian Academy of Sciences)

Abstract

This paper reviews main approaches to risk assessment. The authors accented attention on the nonlinear approach to the theory of risks. It is proposed to define economic risk as the probability of threats that could have material adverse effect on the economic system under study and to change its current state. The method and the program product designed by the authors integrate a wide range of indicators of economic and financial activities at the regional level in the program-technical complex. This paper describes a new method for assessing synergistic and prediction of risk over long time rows of economic indicators at the regional level, including methods of nonlinear and chaotic dynamics, enabling a pseudo-phase and phase portraits, to determine the volatility, to calculate fractal characteristics and predict the behavior of socio-economic indicators with modernized method of Hurst, to model based on recovery probability distribution function of nonequilibrium potential function, to determine the local and global stability of the regional economy and to identify risks as the probability of the threats of an economic nature.

Suggested Citation

  • Gennadiy Bystray & Ivan Lykov & Natalya Nikulina, 2012. "Risks assessment and forecasting long time rows of economic indicators," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(3), pages 240-249.
    • Handle: RePEc:ura:ecregj:v:1:y:2012:i:3:p:240-249
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    Cited by:

    1. Raisa Nifantova, 2013. "Methodological foundations and Modern methods of the population projection," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(2), pages 185-192.

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