Науковий вісник НГУ

Analysis of mathematical methods for describing financial flows: dynamic modeling of an innovative company

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Category: Content №5 2024

Last Updated on 29 October 2024

Published on 30 November -0001

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Authors:

I.S.Pozhuieva, orcid.org/0000-0002-9337-0443, National University “Zaporizhzhia Polytechnic”, Zaporizhzhia, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

T.I.Levytska*, orcid.org/0000-0002-8002-156X, National University “Zaporizhzhia Polytechnic”, Zaporizhzhia, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2024, (5): 177 - 183

https://doi.org/10.33271/nvngu/2024-5/177

Abstract:

Purpose. Development of a dynamic mathematical model of an innovative company operating in accordance with Ukrainian legislation, allowing for the analysis and adjustment of its financial activities.

Methodology. When developing a model and description of financial flows, a factor analysis of the necessary indicators of the financial condition of the enterprise in question was carried out, which were used in the calculations of the presented mathematical modeling. A mathematical apparatus has been developed for calculating financial indicators depending on time. Using inductive, deductive and logical methods, an analysis of the financial situation for the year was carried out.

Findings. The main methods and tools for describing financial flows have been analyzed. Mathematical modeling of the innovative company is carried out, which allows analyzing the costs of the enterprise and determining the size of its free funds. The calculation of financial indicators of the enterprise, which are demonstrated in the form of tables, is performed and the dynamics is shown in charts and graphs. All calculations were made on the basis of existing Ukrainian legislation using modern information technologies.

Originality. A mathematical dynamic model of changes in financial flows at the enterprise has been developed and implemented. The proposed model takes into account various items of expenses and profits in accordance with the state legislation. Calculations allow for dynamic analysis and determination of the impact of various indicators on the financial condition of the enterprise, which allows for faster adoption and implementation of decisions in managing financial flows. This dynamic model is a convenient tool for any enterprise in Ukraine.

Practical value. The results that were obtained during the study can become the basis for creating the necessary digital tools for researching, analyzing and adjusting the financial flows of a particular enterprise. Now methods are available that allow analyzing and describing financial flows more accurately and forecasting their changes in the future. The methodology presented allows the creation of dynamic models that can account for complex dependencies between different indicators and forecast the behavior of financial flows in real time. The financial model allows the simulation of cash flows of planned activities and the evaluation of financial planning in advance, taking into account the conducted research. It is straightforward to use and allows the analysis of different scenarios of business development, significantly reducing the time required.

Keywords: financial flows, mathematical model, profit, free financial resources

References:

1. Ghoddusi, H., Creamer, G. G., & Rafizadeh, N. (2019). Machine learning in energy economics and finance: A review. Energy Economics, 81, 709-727. https://doi.org/10.1016/j.eneco.2019.05.006.

2. Pang, X., Zhou, Y., Wang, P., Lin, W., & Chang, V. (2020). An innovative neural network approach for stock market prediction. The Journal of Supercomputing, 76, 2098-2118. https://doi.org/10.1007/s11227-017-2228-y.

3. Semenchuk, T., & Vasiliha, S. (2020). Application of management matrix models for strategic planning of enterprise activities. Technium Social Sciences Journal, 8, 398. https://doi.org/10.47577/tssj.v8i1.532.

4. Kozuk, V., & Solovij, Kh. (2016). Modification of the Boston Consulting Group matrix in the strategic management of an enterprise. Technology Audit and Production Reserves, 1(3(27), 96-102. https://doi.org/10.15587/2312-8372.2016.60886.

5. Krasovskyi, M. A., & Kudrytska, Z. V. (2020). Forecasting Methods in Financial Markets in the Digital Economy. The Problems of Economy, 1(43), 250-256. https://doi.org/10.32983/2222-0712-2020-1-250-256.

6. Muhammed Muti Ur Rehman (2023). Graph theory as a catalyst for effective economic policy development: unveiling the power of network analysis. EPRA International Journal of Multidisciplinary Research (IJMR), 9(1), 25-29.

7. Tiwari, A. K., Boachie, M. K., & Gupta, R. (2021). Network Analysis of Economic and Financial Uncertainties in Advanced Economies: Evidence from Graph-Theory. Advances in Decision Science, 25(1), 188-215. https://doi.org/10.47654/v25y2021i1p188-215.

8. Battiston, S., & Martinez-Jaramillo, S. (2018). Financial networks and stress testing: Challenges and new research avenues for systemic risk analysis and financial stability implications. Journal of Financial Stability, 35, 6-16. https://doi.org/10.1016/j.jfs.2018.03.010.

9. Zhaoying Ouyang (2022). Construction and Application of Economic Management Fuzzy Decision Model Based on Fuzzy Relevance Method. Journal of Mathematics, 2022, 11. https://doi.org/10.1155/2022/9878815.

10. Stepanenko, О. А. (2012). Analysis of the cash flow of project funds by the method of simulation modeling. Visnyk sotsialno-ekonomichnykh doslidzhen, 3(2), 189-194.

11. Ascani, A., Bettarelli, L., Resmini, L., & Balland, P.-A. (2020). Global networks, local specialisation and regional patterns of innovation. Research Policy, 49(8), 104031. https://doi.org/10.1016/j.respol.2020.104031.

12. Rebman Jr, C. M., Booker, Q. E., Wimmer, H., Levkoff, S., McMurtrey, M., & Powell, L. M. (2023). An Industry Survey of Analytics Spreadsheet Tools Adoption: Microsoft Excel vs Google Sheets. Information Systems Education Journal, 21(5), 29-42.

13. Hrybovska, Yu., & Kononenko, Zh. (2023). Application of information systems in enterprise management. Ekonomika ta suspilstvo, (47), 1-7. https://doi.org/10.32782/2524-0072/2023-47-84.

14. Menon, A. (2020). Time Series Analysis in SAP Predictive Analytics. SSRN 3677420, 7. https://doi.org/10.2139/ssrn.3677420.

15. Thakur, J., & Das, P. (2023). Deploying SPSS in Digital Market Analytics: Leveraging IT Tools for Informed Business Strategies. In 2023 3^rd International Conference on Technological Advancements in Computational Sciences (ICTACS), 1277-1282. https://doi.org/10.1109/ICTACS59847.2023.10390498.

16. Sklyaruk, I., & Vovk, N. (2024). Management accounting of business processes in conditions of digitization. Ekonomika ta suspilstvo, (59), 1-8. https://doi.org/10.32782/2524-0072/2024-59-69.

17. Antoniuk, O. R., & Yaroshchuk, А. S. (2022). Accounting organization in small enterprises: experience of Ukraine and foreign practice. Bulletin National University of Water and Environmental Engineering, 3(99), 3-11. https://doi.org/10.31713/ve320221.

18. Prymus, Yu. S., & Golovchenko, Ye. Yu. (2020). Optimization of settlements with suppliers and contractors of enterprises. Ekonomichnyi prostir, (163), 133-137. https://doi.org/10.32782/2224-6282/163-23.

19. Levandovska, O. M. (2023). Cognitive modeling of the economic development of the enterprise. Problems of modern transformations. Series: economics and management, (8), 3-7. https://doi.org/10.54929/2786-5738-2023-8-04-10.

20. Hrytsenko, К., & Hrytsenko, A. (2022). Payments flows system-dynamic model for assessing the efficiency of leasing operations. Ekonomichnyi analiz, 32(4), 115-126. https://doi.org/10.35774/econa2022.04.115.

21. Pulina, Т. (2015). Determination of the competitive position of the enterprise on the world market of metallurgical products. Scientific Bulletin of UNFU, 25(1), 230-239.

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