Regression models application for analysis and forecasting of the financial activity quality indicators of the company

Authors

  • Nataliia V. Kuznietsova Educational and Scientific Complex “Institute for Applied System Analysis” of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine https://orcid.org/0000-0002-1662-1974
  • Zlata S. Chernysh Educational and Scientific Complex “Institute for Applied System Analysis” of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine https://orcid.org/0000-0002-5589-0018

DOI:

https://doi.org/10.20535/SRIT.2308-8893.2020.2.05

Keywords:

regression models, seasonal autoregression model with integrated moving average, linear multiple regression, data processing, heteroskedastic models

Abstract

The company's success forecasting problem based on its financial indicators by regression models was studied in this research. Models based on linear multiple regression, autoregression with moving average, autoregression with integrated moving average, and seasonal model of autoregression with integrated moving average were built to predict the absolute value of financial indicators. An experimental study was performed on real data, and forecasting was made based on regression models. The models based on the method of group method of data handling and autoregressive neural network were developed. Heteroskedastic models with variable volatility such as ARCH and GARCH type were used to predict the volatility of the financial series. Preliminary data processing using the Holt-Winters method and the Kalman filter were applied to improve the model's quality and forecasting accuracy significantly. Authors suggested and developed a combination of seasonal autoregression with integrated moving average and heteroskedastic models that allowed them to consider the seasonal effects and trends inherent in the financial series and obtain high forecasts for financial indicators.

Author Biographies

Nataliia V. Kuznietsova, Educational and Scientific Complex “Institute for Applied System Analysis” of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv

Nataliia Kuznietsova,

Doctor of Technical Sciences, an associate professor at the Department of the Mathematical Methods of System Analysis of Educational and Scientific Complex “Institute for Applied System Analysis” of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine.

Zlata S. Chernysh, Educational and Scientific Complex “Institute for Applied System Analysis” of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv

Zlata Chernysh,

an undergraduate student at Educational and Scientific Complex “Institute for Applied System Analysis” of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine.

References

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Published

2020-09-25

Issue

No. 2 (2020)

Section

Decision making and control in economic, technical, ecological and social systems

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