Change Point Detection of Sustainable Periods of Economic Systems Under the Robust Control
https://doi.org/10.34023/2313-6383-2019-26-2-27-36
Abstract
This article addresses the potential of mathematical and statistical modelling the change point detection in economic systems on the example of UC «RUSAL». Change point prediction of stable or quasi-stable periods of economic systems is necessary for the operational changing of a strategy, tactics and control of the considered economic system. It solves one of the robust control problems, the purpose of which is the synthesis of the regulator that can provide the preservation of output variables of the system within the robust limit for all types of membership functions and the uncertainty of the input data.
The developed algorithm is based on the study of the behavior of residuals of regression models by the observed series of the dynamics of some exponent (as a benchmark was chosen the price of ordinary share). This algorithm is applicable for small volume samples, which, as a rule, are the series of dynamics of exponents of economic systems and also, in the study of non-Gaussian observational models.
Keywords
About the Authors
S. E. KhrushchevRussian Federation
Sergey E. Khrushchev - Cand. Sci. (Phys.-Math.), Docent, Department of Statistics
2/1, Kamenskaya St., Office 5-206, Novosibirsk, 630005
M. A. Alekseev
Russian Federation
Mikhail A. Alekseev - Dr. Sci. (Phys.-Math.), Docent, Head, Corporate Governance and Finance Department
2/1, Kamenskaya St., Office 5-206, Novosibirsk, 630005
O. M. Logachova
Russian Federation
Olga M. Logachova - Cand. Sci. (Phys.-Math.), Docent, Department of Mathematics and Natural Sciences, Novosi-birsk State University of Economics and Management (NSUEM); Docent, Department of Higher Mathematics, Siberian State University of Geosystems and Technologies
2/1, Kamenskaya St., Office 5-206, Novosibirsk, 630005
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Review
For citations:
Khrushchev S.E., Alekseev M.A., Logachova O.M. Change Point Detection of Sustainable Periods of Economic Systems Under the Robust Control. Voprosy statistiki. 2019;26(2):27-36. (In Russ.) https://doi.org/10.34023/2313-6383-2019-26-2-27-36