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Model for Sustainable Financial Planning and Investment Financing Using Monte Carlo Method

Author

Listed:
  • Alica Tobisova

    (Faculty of Aeronautics, Technical University of Kosice, Rampova 7, 041 21 Kosice, Slovakia)

  • Andrea Senova

    (Faculty of Mining, Ecology, Process Control and Geotechnologies, Technical University of Kosice, Letna 9, 042 00 Kosice, Slovakia)

  • Robert Rozenberg

    (Faculty of Aeronautics, Technical University of Kosice, Rampova 7, 041 21 Kosice, Slovakia)

Abstract

The article deals with current issues of finance and investment planning with a selective focus on financial decision-making processes using sophisticated software tools. The article has a special significance in this period when it is necessary to re-evaluate and consider ways of appropriate and effective investment and financial policy in view of the restrictions in enterprises in Slovakia, which brings with it the global pandemic COVID-19 or another crisis in enterprises. The aim of the article is to propose a methodology as a tool for streamlining the investment activities of companies. The proposed methodology combines the usability of traditional and modern economic methods, making it an important tool for the sustainability and competitiveness of enterprises. Three variants of investment decisions in the enterprise were simulated using simulation in terms of two approaches. The first approach focuses on mathematical–economic calculations of deterministic modeling through traditional software tools. The second stochastic modeling uses the simulation of financial risks using a modern software tool using the Monte Carlo method. The output is the creation of a graphical management model in the form of an algorithm.

Suggested Citation

  • Alica Tobisova & Andrea Senova & Robert Rozenberg, 2022. "Model for Sustainable Financial Planning and Investment Financing Using Monte Carlo Method," Sustainability, MDPI, vol. 14(14), pages 1-18, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8785-:d:865463
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    References listed on IDEAS

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    2. Yunyu Zhang, 2020. "The value of Monte Carlo model-based variance reduction technology in the pricing of financial derivatives," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-13, February.
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    4. Emilio Abad-Segura & Mariana-Daniela González-Zamar & Eloy López-Meneses & Esteban Vázquez-Cano, 2020. "Financial Technology: Review of Trends, Approaches and Management," Mathematics, MDPI, vol. 8(6), pages 1-37, June.
    5. Choong‐Yuel Yoo & Jinhan Pae, 2013. "Estimation and Prediction Tests of Cash Flow Forecast Accuracy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(3), pages 215-225, April.
    6. Daniel J Arenas & Lanair A Lett & Heather Klusaritz & Anne M Teitelman, 2017. "A Monte Carlo simulation approach for estimating the health and economic impact of interventions provided at a student-run clinic," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-12, December.
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    Cited by:

    1. Andrea Senova & Alica Tobisova & Robert Rozenberg, 2023. "New Approaches to Project Risk Assessment Utilizing the Monte Carlo Method," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    2. Mário Molokáč & Enikő Kornecká & Henrieta Pavolová & Tomáš Bakalár & Miloš Jesenský, 2023. "Online Marketing of European Geoparks as a Landscape Promotion Tool," Land, MDPI, vol. 12(4), pages 1-22, April.

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