Articles

The research of industrial production dynamics based on the tools of chaos theory

User Rating:  / 0
PoorBest 

Authors:


O.Yankovyi*, orcid.org/0000-0003-2413-855X, Odesa National Economic University, Odesa, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

N.Basiurkina, orcid.org/0000-0001-9342-8863, Odesa National University of Technology, Odesa, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

H.Karpinska, orcid.org/0000-0003-4896-1866, Institute of Market And Economic & Ecological Researches of the National Academy of Sciences of Ukraine, Odesa, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

L.Malyshenko, orcid.org/0009-0006-1249-7714, Odesa Professional College of Trade and Economic, Odesa, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

V.Chernova, orcid.org/0000-0001-7142-8029, Odesa National Economic University, Odesa, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.


повний текст / full article



Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2024, (2): 133 - 139

https://doi.org/10.33271/nvngu/2024-2/133



Abstract:



Purpose.
To prove the possibility of improving the procedure for analyzing and forecasting the dynamics of economic systems through the comprehensive use of scientific achievements of chaos theory, namely: checking the trend stability of time series, studying their phase space, attractors, Lyapunov’s chaos indicators, the maximum length of a reliable forecast of the socio-economic system development, etc.


Methodology.
The methodological basis of the study is the provisions of modern economic theory, in particular, statistics, economic and mathematical modeling and forecasting, economic cybernetics and systems theory, fundamental works of foreign and domestic scientists on the issues of fractal analysis and chaos theory.


Findings.
The phase and fractal analysis of the dynamics series of chain and basic growth rates of industrial production in Ukraine was carried out, and their fractal dimension was determined. The correlation function was calculated and Lyapunov’s indicators were found to assess the degree of chaotic system, Kolmogorov entropy, and the parameter of evolution in time. The maximum length of a reliable forecast and the future values of the time series were also determined.


Originality.
The article substantiates the necessity and possibility of applying the methodological apparatus of chaos theory in the process of analyzing and forecasting economic dynamics, including the development of domestic industrial production.


Practical value.
The value of the work is determined by the applied aspects of reliable forecasts of chain and basic growth rates of industrial production in Ukraine obtained on the basis of the chaos theory tools, the possibility of comparative analysis of the domestic industry development in “potential peacetime” and actual wartime.



Keywords:
nonlinear dynamic systems, chaos theory, economic dynamics, persistence of time series

References.


1. Nayman, E. (2009). Calculation of the Hurst exponent to identify trendiness (persistence) of financial markets and macroeconomic indicators. Ekonomíst, (10), 25-29.

2. Krytsun, K. (2014). Aspects of use of fractal analysis in the currency market of Ukraine. Visnyk Kyyivskoho Natsionalnoho Universytetu imeni Tarasa Shevchenka, (7), 48-53.

3. Krytsun, K. I. (2016). Multifractal analysis of the dynamics of the stock indexes: PFTS and UX in the Ukrainian stock market. Efektyvna ekonomika, 1-8.

4. Nych, L. Ya., & Kaminskyy, R. M. (2015). Determination of Hurst index using the fractal dimension calculated by the cellular method on the example of short time series. Visnyk Natsionalnoho Universytetu Lvivska Politekhnika. Seriya: Informatsiyni systemy ta merezhi, 814(1), 100-111.

5. Harder, S. Ye., & Kornil, T. L. (2018). Fractal analysis and trend forecasting of financial time series. Visnyk Natsionalnoho Tekhnichnoho Universytetu “KHPI”. Matematychne modelyuvannya v tekhnitsi ta tekhnolohiyakh, 3(1279), 37-40. Kharkiv.

6. Kudzinovsʹkyy, A. S., & Morozyuk, A. V. (2021). Application of the Hurst parameter to study the dynamics of financial markets. POLIT. Challenges of science today, 169-170.

7. Kirichenko, L., & Radivilova, T. (2018). Estimating the self-similarity parameter for stationary stochastic processes. International Journal “Information Content and Processing”, 5(1), 41-71.

8. Yankovyі, O. G., & Honcharenko, O. M. (2012). Analysis of the sustainable development of enterprises using the normalized Hurst range method. Visnyk Vinnytskoho Politekhnichnoho Instytutu, (2), 35-38.

9. Chaykovsʹka, I. I. (2014). Fractal analysis and trends in innovative process at industrial enterprises. Ekonomichnyy chasopys-XXI, 7-8(2), 65-68.

10. Yastremsʹka, O. M., & Demchenko, H. V. (2016). Fractal analysis of the innovation activity of the industrial enterprises of Kharkiv region and trends of development. Prychornomorsʹki ekonomichni studiyi, (11), 186-190.

11. Demydenko, O. V. (2017). Fractal analysis of climatic parameters and productivity of grain crops. Visnyk ahrarnoyi nauky, (7), 10-16.

12. Kryvda, O. V., Sydorenko, Yu. V., & Romanova, D. P. (2017). Forecasting the dynamics of economic processes using the methods of fractal geometry. Ekonomichnyi Visnyk NTUU “KPI”: zbirnyk naukovykh prats, (14), 483-490. https://doi.org/10.20535/2307-5651.14.2017.108714.

13. Brovarets’, O. O., & Chovnyuk, Yu. V. (2020). The use of fractal analysis methods in the study of electrical conductivity of soils and the yield of agricultural crops. Silʹsʹkohospodarsʹki mashyny, (45), 23-33. https://doi.org/10.36910/acm.vi45.378.

14. Skalozub, V. V., Horyachkin, V. M., Klymenko, I. V., & Shapo­val, D. O. (2022). Models and procedures for classification and forecasting of nondeterministic processes according to chaotic dynamics parameters. Systemni tekhnolohiyi, 3(140), 104-123. https://doi.org/10.34185/1562-9945-3-140-2022-10.

15. Tan, X. (2021). Predictive Analysis of Economic Chaotic Time Series Based on Chaotic Genetics Combined with Fuzzy Decision Algorithm. https://doi.org/10.1155/2021/5517502.

16. Bil’s’ka, O. V. (2020). Research of the behavior of national economy subjects on-line frequency request for exchange rates methods of analysis of pseudophase space. Elektronne fakhove vydannya “Efektyvna ekonomika”, (7). https://doi.org/10.32702/2307-2105-2020.7.16.

17. Serhiyenko, O. A., Mashchenko, M. A., & Baranova, V. V. (2021). Modeling the Instability of Development of Complex Hierarchical Systems. Problemy ekonomiky, 1(47), 143-154. https://doi.org/10.32983/2222-0712-2021-1-143-154.

18. Soloviev, V., Serdiuk, О., Semerikov, S., & Kiv, A. (2020). Recurrence plot-based analysis of financial-economic crashes. CEUR Workshop Proceedings, 21-40.

19. State Statistics Service of Ukraine. Retrieved from https://www.ukrstat.gov.ua/.

20. Danylov, V. Ya., Zinchenko, A. Yu., & Danilov, V. Ya. (2017). Systematic approach to solving direct and inverse problems in systems with chaos. Systemni doslidzhennya ta informatsiyni tekhnolohiyi, (2), 7-18. https://doi.org/10.20535/SRIT.2308-8893.2017.2.01.

21. Solovyov, V. M., & Stratiychuk, I. O. (2013). Use of precursor indicators of crisis phenomena of the financial market on the basis of the scale-dependent Lyapunov exponent. Problemy ekonomiky, (2), 279-283.

22. Solovyov, V. M., & Serdyuk, O. A. (2019). The models of application of the recurrence entropy and recurrence period density entropy to the analysis of complex systems dynamics. Visnyk Cherkaskoho Natsionalnoho Universytetu imeni Bohdana Khmelnytskoho, (2), 20-34. https://doi.org/10.31651/2076-5886-2019-2-20-34.

23. Tkachuk, N. (2022). Entropic processes in ensuring self-organization of the banking system. International Science Journal of Management, Economics & Finance, 1(4), 1-8. https://doi.org/10.11648/j.isjea.20220104.01.

 

Visitors

7502341
Today
This Month
All days
2997
24827
7502341

Guest Book

If you have questions, comments or suggestions, you can write them in our "Guest Book"

Registration data

ISSN (print) 2071-2227,
ISSN (online) 2223-2362.
Journal was registered by Ministry of Justice of Ukraine.
Registration number КВ No.17742-6592PR dated April 27, 2011.

Contacts

D.Yavornytskyi ave.,19, pavilion 3, room 24-а, Dnipro, 49005
Tel.: +38 (056) 746 32 79.
e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
You are here: Home