DOI: 10.33917/mic-4.117.2024.65-71

Presents an analysis of methods for reducing financial losses in a company; types of risks are systematized; an algorithm for monitoring and minimizing financial risks is presented using the Altman model and the Taffler model as an example.

References:

1. Galimulina F.F., Zhukovskaya I.V., Komissarova I.P., Shinkevich A.I., Mayorova A.N., Astafyeva I.A., Klimova N.V., Nabiullina K.R. Technology Platforms as an Efficient Tool to Modernize Russia’s Economy. International Journal of Economics and Financial Issues. 2016;6(1):163–168.

2. Zhukovskaya I.V. Specifics of Investment Project Risk Management in Industry. Economics and Management. 2010;2:53–56.

3. Financial Risk Management: Textbook and Workshop for Universities / I.P. Khominich [et al.]; edited by I.P. Khominich. 3rd ed., revised and enlarged. Moscow: Yurait Publishing House, 2024. 582 p.

4. Data from the electronic database system «Kontur-Fokus» and «SBIS».

DOI: 10.33917/mic-2.103.2022.58-64

The article considers the issue of forming the optimal structure of assets of manufacturing enterprises according to the goals of their owners. An original approach is proposed to optimize the structure of the company’s assets according to the criterion of maximizing their effectiveness for owners through the enterprise capitalization indicator.

To link the indicators of capitalization and profit from the existing assets of manufacturing enterprises of the manufacturing industry, the authors propose to create a multiple regression model, where the independent variable is capitalization (profit), the dependent ones are indicators of specific assets.

After finding the contributions (regression coefficients) of each asset, we propose to form their structure according to the principle of a portfolio approach, in which the efficiency indicator of all assets will strive to the maximum and at the same time the specific features of the enterprise in each case will be taken into account [10].

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2. Bezpalov V.V., Dorofeev A.Yu., Gorin D.S., Marien L.S. Designing stages of anti-crisis organizational engineering of agricultural enterprises within the universal management cycle. Journal of Applied Research. 2021;1(4):22-35. (In Russ.).

3. Blazhevich O.G. Turnover indicators and their significance for assessing the efficiency of asset use // Scientific Bulletin: Finance, Banks, Investments. 2018;4 (45):31-38. (In Russ.).

4. Brigham Yu., Erhardt M. Financial management: St. Petersburg: Peter, 2009. (In Russ.).

5. Voloshchuk L.A., Tkachev S.I., Monina O.Yu. Statistics. Educational and practical manual: Saratov, 2016. (In Russ.).

6. Van Horn D., Vakhovich D. Fundamentals of Financial Management: M.: Dialectics, 2020. (In Russ.).

7. Dorofeev A.Yu., Filatov V.V., Medvedev V.M., Shestov A.V., Fadeev A.S. Methodology for calculating the discount rate using the capital asset valuation model. Online journal of Science Studies. 2015;7(2 (27)):18. (In Russ.).

8. Mukhidov R.H., Simonova V.A., Filatov V.V. Initial public offering of securities as a financial instrument of Russian corporations for attracting investments // Collection of scientific papers Actual issues of economics, commerce and service, Kosygin Russian State University, 2021. pp. 124-128. (In Russ.).

9. Samuelson P., Nordhaus U. Economics: M: Williams, 2018. (In Russ.).

10. Simonova V.A. Methods of optimization of technological assets of business processes of industrial enterprises // Transport business of Russia. 2010;5:68-71. (In Russ.).

11. Simonova V.A. Efficiency assessment and optimization of business processes of food industry enterprises // Economics, statistics and computer science. Bulletin of UMO. 2012;2:177-183. (In Russ.).

12. Simonova V.A., Tomm V.A. Normative values of financial coefficients as a basis for the formation of the balance sheet structure of industrial enterprises // Modern humanitarian studies. 2013;4 (53):29-34. (In Russ.).

DOI: 10.33917/mic-3.92.2020.12-19

In modern conditions of increasing role of digitalization, the issue of choosing priority areas for the digital technologies’ implementation is urgent in order to increase the competitiveness of the enterprises. Given the strategic importance of the enterprises of the space industry, the aim of the study is to develop a model for highlighting the priority areas of digitalization, which are most effective for increasing the share of digitalization of production processes. For this, economically-mathematically methods and functional dependencies are used. Based on the results of the study, the authors presented an economic and mathematical model of the dynamics of the digital technologies implementation, the economic analysis of the application of this model is carried out and proposed an approach to highlighting the priority areas of digitalization.