Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/266866 
Year of Publication: 
2021
Citation: 
[Journal:] Financial Internet Quarterly [ISSN:] 2719-3454 [Volume:] 17 [Issue:] 1 [Publisher:] Sciendo [Place:] Warsaw [Year:] 2021 [Pages:] 62-69
Publisher: 
Sciendo, Warsaw
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.
Subjects: 
multifactor regression
forecasting revenue
correlational and regression analysis
JEL: 
A01
C01
C05
C06
C08
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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