Determination of Industry Indicators of Financial Analysis of Enterprises (on the Example of the Industry for the Production of Crude Oil and Natural Gas)
https://doi.org/10.21686/2500-3925-2020-3-13-24
Abstract
The aim of the study is the development of theoretical and methodological principles of the analysis of industry financial indicators. The relevance of the topic is confirmed on the one hand by the demand for industry indicators for all persons interested in financial and comparative analysis of enterprises, on the other hand by the complexity and lack of methods for deriving industry indicators of the financial analysis of enterprises.
Materials and methods. The study used a system and comparative analysis, methods of economic and financial analysis of the financial statements of enterprises in the industry, and methods of statistical evaluation of the main parameters of the sample with a lognormal distribution. The main attention is paid to the use of multivariate statistical analysis, the use of the model of lognormal distributions recommended for distributions with pronounced right-hand asymmetry. As the statistical material, the accounting data of the enterprises of the industry for the extraction of crude oil and natural gas for 2016 were used. The sample size was 185 enterprises. In the course of the study, the authors solved the following tasks: proposed stages of analysis for determining industry financial indicators, tested the hypothesis of a lognormal distribution of marginal distributions of the main financial indicators of the sample, tested the hypothesis of a jointly normal distribution of a multi-factor random vector of financial indicators of the sample, obtained the most likely values of financial analysis indicators for the industry of crude oil and natural gas production.
Results. The theoretical significance of the work is the algorithm proposed by the authors for calculating industry-specific indicators of financial analysis, characterized by obtaining modal values based on the analysis of the multidimensional logarithmically normal distribution of the vector of financial indicators of a sample of enterprises. In the course of the study, the authors obtained distributions for the main indicators with a pronounced right-hand asymmetry and tested the hypothesis of the lognormal distribution of marginal distributions. The paper presents an algorithm for testing the hypothesis of joint normality of a ninedimensional random vector. Median and modal values of industry and financial indicators were obtained. The authors analyzed the differences between the median and modal results of the study. For analysis, a three-dimensional random vector is considered, including revenue, return on equity and turnover of accounts receivable. The difference between median and modal results is explained by the right-hand asymmetry of the distribution. The recommendations, given by the authors for determining industry indicators of financial analysis of enterprises in the industry for the extraction of crude oil and natural gas are practical in nature and are applicable to all industries.
Conclusion. In the work, it is shown that the orientation toward generally established recommended values of coverage indicators, financial leverage, immobilization, profitability and turnover seems incorrect due to the variety of specific features of enterprises in various industries. We recommend calculating the most likely industry coefficients by groups depending on the size of the enterprise (revenue or capitalization).
About the Authors
N. A. BukharinRussian Federation
M. B. Laskin
Russian Federation
Nikolay A. Bukharin Cand. Sci. (Technical sciences), Director of the MIPK center
S. V. Pupentsova
Russian Federation
Svetlana V. Pupentsova Cand. Sci. (Economics), Associate Professor SPbPU
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Review
For citations:
Bukharin N.A., Laskin M.B., Pupentsova S.V. Determination of Industry Indicators of Financial Analysis of Enterprises (on the Example of the Industry for the Production of Crude Oil and Natural Gas). Statistics and Economics. 2020;17(3):13-24. (In Russ.) https://doi.org/10.21686/2500-3925-2020-3-13-24