IDEAS home Printed from https://ideas.repec.org/a/vaj/journl/v5y2010i1p110-131.html
   My bibliography  Save this article

Model for Use of Monte Carlo Simulations in Business Valuation

Author

Listed:
  • Daniel MANATE
  • Pavel FARCAS

Abstract

This paper shows the results of the numerical simulations carried out on a discounted cash flow-based enterprise valuation model created by the authors. It describes all the steps of a Monte Carlo type simulation in estimating equity capital value of an issuer listed on the Bucharest Stock Exchange (BSE). Simulated random variables had a great impact on the output variables. Input random variables were characterized by distribution functions deemed appropriate and by moments of order of I and II, obtained from historical data. The operating revenues distribution function is uniform and symmetrical around the estimated values, cantered on these values with a variation of +- 20%. This function was also considered adequate for the variation in the percentage of the net working capital (NWC) in operating revenues. For non-operating assets a Gaussian distribution function and for the Enterprise Value/Earnings Before Interest, Taxes Depreciation and Amortization multiple (EV/EBITDA) an asymmetric triangular distribution function were used, based on multiples of the median values that are characteristic of the enterprises in Central and Eastern Europe (CEE ). One single output variable, i.e. the equity capital market value, was selected. The case study concluded with an analysis of the results obtained by simulation.

Suggested Citation

  • Daniel MANATE & Pavel FARCAS, 2010. "Model for Use of Monte Carlo Simulations in Business Valuation," The Valuation Journal, The National Association of Authorized Romanian Valuers, vol. 5(1), pages 110-131.
  • Handle: RePEc:vaj:journl:v:5:y:2010:i:1:p:110-131
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kaczmarzyk Jan, 2019. "Several Sets of Assumptions for the Monte Carlo Simulation for a More Precise Analysis of Enterprise Risk," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 23(4), pages 80-95, December.

    More about this item

    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    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:vaj:journl:v:5:y:2010:i:1:p:110-131. 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: Stefan Alexandru (email available below). General contact details of provider: https://edirc.repec.org/data/anevaea.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.