IDEAS home Printed from https://ideas.repec.org/a/nwe/iisabg/y2022i1p111-131.html
   My bibliography  Save this article

Application of Simulation-based Approach for Determining the Value of Companies Operating in an Environment of Uncertainty

Author

Listed:
  • Petar Rangelov

    (University of National and World Economy, Sofia, Bulgaria)

Abstract

The article focuses on a specific valuation technique based on probabilistic simulation of value-relevant factors determining the intrinsic value of companies. In this paper I present the practical aspects and relevant problems related to the application of this type of valuation methods. Basic probabilistic processes applicable to different enterprises depending on their economic characteristics are analyzed. In the practical part, the presented evaluation technique is applied for evaluation of a Bulgarian pharmaceutical company, as the main advantages and results are presented.

Suggested Citation

  • Petar Rangelov, 2022. "Application of Simulation-based Approach for Determining the Value of Companies Operating in an Environment of Uncertainty," Ikonomiceski i Sotsialni Alternativi, University of National and World Economy, Sofia, Bulgaria, issue 1, pages 111-131, March.
    • Handle: RePEc:nwe:iisabg:y:2022:i:1:p:111-131
    as

    Download full text from publisher

    File URL: https://www.unwe.bg/doi/alternativi/2022.1/ISA.2022.1.10.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Monte Carlo simulation; Ornshtain-Ulenbeck process; free cash flow to the firm model; enterprise value;
    All these keywords.

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nwe:iisabg:y:2022:i:1:p:111-131. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Vanya Lazarova (email available below). General contact details of provider: https://edirc.repec.org/data/unweebg.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.