TIME SERIES IN FORECASTING THE VOLUMES OF INVESTMENTS
Abstract
The purpose of the work is to develop decision-making models for the investment management of the land reclamation system, which, based on the analysis of statistical data, will allow making forecasts and recommendations. That is, the purpose of the work is to present a mathematical model of a time series for predicting the volume of investments in land reclamation in Kazakhstan.
Methodology is methods for analyzing Republic are analyzed from the point of view of justifying the time series, namely, spectral, regression and correlation analysis, models of the moving average and autoregression.
Originality / value are the proposed model effectively takes into account the mutual influence of the elements of the dynamic range of small agricultural formations affecting the increase in competitiveness, that is, the influence of different economic parameters on each other while they are simultaneously manifested. In this case, the predictive operator is actually trained on the statistical material of the past.
Conclusions - on the basis of the prognostic information obtained, investments in the land reclamation of the Republic will be able to increase the validity, objectivity and efficiency of decision making in business processes related to contracting and planning in forecasting the volumes of the agro-industrial complex of Kazakhstan, as well as using the Republic’s agricultural resources most effectively.
About the Authors
S. K. Burgumbayeva
Eurasian National University named after L. N. Gumilev
Kazakhstan
Kazakhstan
PhD, associate Professor of Higher mathematics»
Astana
A. S. Iskakova
Eurasian National University named after L. N. Gumilev
Kazakhstan
Kazakhstan
Candidate of physical and mathematical Sciences, associate Professor of " Fundamental mathematics»
Astana
D. G. Dzhumabaev
Eurasian National University named after L. N. Gumilev
Kazakhstan
Kazakhstan
Candidate of physical and mathematical Sciences, associate Professor of Higher mathematics»
Astana
A. M. Batyrbekova
Eurasian National University named after L. N. Gumilev
Kazakhstan
Kazakhstan
Candidate of economic Sciences, associate Professor of " Management»
Astana
References
1. Шейнин Л. Об эффективности земельно-мелиоративных преобразований //Общество и экономика. – 2010. – №. 10-11. – С. 200-210.
2. Сенниковa М. Н., Омарова Г. Е. Обеспечение продовольственной безопасности Казахстана путем интегрированного управления водными ресурсами //Проблемы постсоветского пространства. – 2018. – Т. 5. – №. 3. – С. 268-283.
3. Мустафаев Ж. С., Есполов Т. И., Козыкеева А. Т. Проблемы и пути решения мелиорации сельскохозяйственных земель в Казахстане //Мелиорация и водное хозяйство: проблемы и пути решения. – 2016. – С. 339-344.
4. http://stat.gov.kz/faces/wcnav_externalId/ecolog-C-8?_afrLoop=5903019947150759#%40%3F_afrLoop%3D5903019947150759%26_adf.ctrl-state%3D5ovbqg8ty_111
5. Носков В.П. Эконометрика: Книги 1 и 2. - М.: Издательский дом «Дело» РАНХиГС, 2011. Кн.1-672 с., Кн. 2 - 576 с.
6. Дрейпер И., Смит Г. Прикладной регрессионный анализ: Пер. с англ. — Кн. 1, 2. — М.: Финансы и статистика,1987.
7. Ферстер Э,, Ренц Б, Методы корреляционного и регрессионного анализа: Пер. с нем. — М.: Финансы и статистика, 1982.
8. Лоскутов А.Ю. Михайлов А.С., «Остовы теории сложных систем – Москва, Регулярная и хаотичная динамика», 2007.
9. А.А. Самарский, А.П. Михайлов, «Математическое моделирование», 2002.
10. Iskakova A.S., Burgumbayeva S.K., Dzhumabayeva D.G., Zhumadilov M.T. Model of quadratic programming of economic factors affecting the competitiveness of small-scale agricultural enterprises//Central Asian Economic Review (CAER), №4 (122), 2018, С.10-16.
11. Ayman, Iskakova. "Statistical Research for Probabilistic Model of Distortions of Remote Sensing." Journal of Physics: Conference Series. Vol. 738. No. 1. IOP Publishing, 2016.
12. Ayman, Iskakova. "Construction of the most suitable unbiased estimate distortions of radiation processes from remote sensing data." Journal of Physics: Conference Series. Vol. 490. No. 1. IOP Publishing, 2014.
13. Iskakova A., Zhaxybayeva G. Maximum likelihood estimates of some probability model of discrete distributions. – 2018.
14. Burgumbaeva S. A tri-harmonic Neumann function for the unit disc //AIP Conference Proceedings. – AIP Publishing, 2018. – Т. 1997. – №. 1.
15. Sánchez-Prieto J. et al. Control of blood pressure by using an intelligent telephone application with feedback and competitiveness strategy. HTApp Control project //Semergen. – 2018. – Т. 44. – №. 1. – С. 30-36.
16. Bernal-Conesa J. A., de Nieves Nieto C., Briones-Peñalver A. J. CSR strategy in technology companies: its influence on performance, competitiveness and sustainability //Corporate Social Responsibility and Environmental Management. – 2017. – Т. 24. – №. 2. – С. 96-107.
Review
For citations:
Burgumbayeva S.K., Iskakova A.S., Dzhumabaev D.G., Batyrbekova A.M. TIME SERIES IN FORECASTING THE VOLUMES OF INVESTMENTS. Central Asian Economic Review. 2019;(1):157-163. (In Russ.)
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