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Risk Management in Business Valuation in the Context of Digital Transformation

Author

Listed:
  • Pupentsova Svetlana V.

    (Institute of Industrial Management, Economics and Trade Peter the Great St. Petersburg Polytechnic University)

  • Gromova Elizaveta A.

    (Institute of Industrial Management, Economics and Trade Peter the Great St. Petersburg Polytechnic University)

Abstract

The paper deals with business valuation in unstable conditions of the external environment. Economic recession and the need for digital transformation is coming to the fore in Russia. As a result of this, the valuation of assets and business acquires additional complexity and issues related to effective risk assessment become relevant. The main objective of this paper is to offer non-traditional methods of risk assessment for business valuation at the moment. The qualitative and quantitative risk analysis will help to improve the quality of the assessment reports of the property in an unstable period. The paper focuses on the non-traditional methods of risk assessment (Monte Carlo method, game theory) which must be used in determining the market value of the object of assessment in the current time. A practical example of using the simulation modeling method is given in detail. Summarizing, the use of the simulation modeling method for calculating the market value of the appraisal object will provide additional (compared to the standard method) information and increase the reliability of the results. Moreover, in the period of the coronavirus pandemic, this paper becomes even more relevant and important, seeing as how uncertainty is becoming inherent in countries around the world. Thus, this study is of value to researchers in the field of economic modeling and appraisers across the globe.

Suggested Citation

  • Pupentsova Svetlana V. & Gromova Elizaveta A., 2021. "Risk Management in Business Valuation in the Context of Digital Transformation," Real Estate Management and Valuation, Sciendo, vol. 29(2), pages 97-106, June.
    • Handle: RePEc:vrs:remava:v:29:y:2021:i:2:p:97-106:n:6
    DOI: 10.2478/remav-2021-0016
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    References listed on IDEAS

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    1. repec:ers:journl:v:xx:y:2017:i:2b:p:397-411 is not listed on IDEAS
    2. Kęstutis Peleckis, 2015. "The Use of Game Theory for Making Rational Decisions in Business Negotiations: A Conceptual Model," Entrepreneurial Business and Economics Review, Centre for Strategic and International Entrepreneurship at the Cracow University of Economics., vol. 3(4), pages 105-121.
    3. Alvin E. Roth & Robert B. Wilson, 2019. "How Market Design Emerged from Game Theory: A Mutual Interview," Journal of Economic Perspectives, American Economic Association, vol. 33(3), pages 118-143, Summer.
    4. Danielsson, Jon & James, Kevin R. & Valenzuela, Marcela & Zer, Ilknur, 2016. "Model risk of risk models," Journal of Financial Stability, Elsevier, vol. 23(C), pages 79-91.
    5. A. Maron & M. Maron, 2019. "Minimizing the Maximum Risk of Currency Conversion for a Company Buying Abroad," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 59-67.
    6. Helena Gaspars-Wieloch, 2018. "The Impact of the Structure of the Payoff Matrix on the Final Decision made Under Uncertainty," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(01), pages 1-27, February.
    7. Alexander Chursin & Yuri Vlasov & Yury Makarov, 2017. "Innovation as a Basis for Competitiveness," Springer Books, Springer, number 978-3-319-40600-8, September.
    8. Olga Romanova, 2018. "Industrial Policy Priorities of Russia in the Context of Challenges of the Fourth Industrial Revolution. Part 1," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(2), pages 420-432.
    9. Olga Romanova, 2018. "Industrial Policy Priorities of Russia in the Context of Challenges of the Fourth Industrial Revolution. Part 2," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(3), pages 806-819.
    10. Liudmila Vasilevna Nikolova & Dmitriy Grigorievich Rodionov & Natalya Vladimirovna Afanasyeva, 2017. "Impact of Globalization on Innovation project Risks Estimation," European Research Studies Journal, European Research Studies Journal, vol. 0(2B), pages 396-410.
    11. Filippo Curti & Ibrahim Ergen & Minh Le & Marco Migueis & Rob T. Stewart, 2016. "Benchmarking Operational Risk Models," Finance and Economics Discussion Series 2016-070, Board of Governors of the Federal Reserve System (U.S.).
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    More about this item

    Keywords

    business valuation; market value; risks; simulation modeling method; Russian economy; digital transformation;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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