Comprehensive Analysis of a Company's Activity by Means of Statistical Modeling as Support for its Decision-Making System

Soboń Janusz, Burkina Natalia, Sapun Kostiantyn and Seleznova Ruslana
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Soboń Janusz: AJP w Gorzowie Wielkopolskim, Poland
Burkina Natalia: Donetsk National University after V. Stus, Ukraine
Sapun Kostiantyn: Varna Free University, Bulgaria
Seleznova Ruslana: Taras Shevchenko Kiev National University, Ukraine.

Financial Internet Quarterly (formerly e-Finanse), 2021, vol. 17, issue 1, 62-69

Abstract: An important role in ensuring effective forms of management and increasing competitiveness is played by the process of forecasting the activity of the enterprise. This work analyzed the performance of a food industry enterprise, for which a wide range of statistical methods were applied such as methods of cluster, correlational and regression analysis, statistical tests of Fisher, Student, Farrar-Glauber, Durbin-Watson, Goldfeld-Quandt, μ-criterion, multifactor regression, trend, auto-regression models, and models of seasonal fluctuations, which provided a view of the economic properties of the enterprise profit process, in particular the auto-regression component of revenue dependence on its value last year, seasonal quarterly dependence on sales and marketing costs, product price, etc. The detected patterns will allow us to take into account these features for forecasting future revenues and for adjusting the enterprise’s decision-making system taking into account seasonal features and results of the previous year.

Keywords: multifactor regression; forecasting revenue; correlational and regression analysis (search for similar items in EconPapers)
JEL-codes: A1 C1 C5 C6 C8 (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:finiqu:v:17:y:2021:i:1:p:62-69:n:2

DOI: 10.2478/fiqf-2021-0007

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