IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v16y2023i3p140-d1075564.html
   My bibliography  Save this article

Forecasting Methods of Key Ratios and Their Impact in Company’s Value

Author

Listed:
  • Angelos Liapis

    (Department of Accounting and Finance, Athens University of Economics and Business, 104 34 Athens, Greece)

  • Stylianos Artsidakis

    (Department of Economic & Regional Development, Panteion University, Syngrou Av., 176 71 Athens, Greece)

  • Christos Galanos

    (Department of Economic & Regional Development, Panteion University, Syngrou Av., 176 71 Athens, Greece)

Abstract

This paper aims to develop a comprehensive procedure for calculating the fair value of a company by predicting its future values using historical data of key ratios and applying dynamic algorithms to improve the selection of forecasting methods. The most important business valuation methodologies are based on discounting a firm’s future variables, and there are many ways to predict them through financial and quantitative methodologies. This paper provides the most important and commonly used time series forecasting methodologies that can be used for variables, such as financial ratios, and proposes three different algorithms to help and improve the selection of the best-fit method for each of the model’s variables. Another, more indirect way of predicting values is using operational research methodologies, such as Monte Carlo simulation, where the output of the sensitivity analysis gives the most likely firm value, taking into account the distribution of each variable. This paper includes a complete example of using the above procedures in a real Greek company to calculate its fair value. It offers alternative approaches to the problem that exists around the process of predicting variables, with the help of technology. We hope this will be a useful tool for future use.

Suggested Citation

  • Angelos Liapis & Stylianos Artsidakis & Christos Galanos, 2023. "Forecasting Methods of Key Ratios and Their Impact in Company’s Value," JRFM, MDPI, vol. 16(3), pages 1-17, February.
  • Handle: RePEc:gam:jjrfmx:v:16:y:2023:i:3:p:140-:d:1075564
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/16/3/140/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1911-8074/16/3/140/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Marco Del Negro & Marc P. Giannoni & Frank Schorfheide, 2015. "Inflation in the Great Recession and New Keynesian Models," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 168-196, January.
    2. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2018. "Diagnostic Expectations and Credit Cycles," Journal of Finance, American Finance Association, vol. 73(1), pages 199-227, February.
    3. Jeffrey C. Fuhrer, 2018. "Intrinsic expectations persistence: evidence from professional and household survey expectations," Working Papers 18-9, Federal Reserve Bank of Boston.
    4. Bruggemann, Ralf & Lutkepohl, Helmut & Saikkonen, Pentti, 2006. "Residual autocorrelation testing for vector error correction models," Journal of Econometrics, Elsevier, vol. 134(2), pages 579-604, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:zbw:bofrdp:2018_022 is not listed on IDEAS
    2. Hagenhoff, Tim & Lustenhouwer, Joep, 2023. "The role of stickiness, extrapolation and past consensus forecasts in macroeconomic expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    3. Constantin Bürgi & Julio L. Ortiz, 2022. "Overreaction through Anchoring," CESifo Working Paper Series 10193, CESifo.
    4. Hagenhoff, Tim & Lustenhouwer, Joep, 2020. "The role of stickiness, extrapolation and past consensus forecasts in macroeconomic expectations," Working Papers 0686, University of Heidelberg, Department of Economics.
    5. Francesco Bianchi & Sydney C. Ludvigson & Sai Ma, 2022. "Belief Distortions and Macroeconomic Fluctuations," American Economic Review, American Economic Association, vol. 112(7), pages 2269-2315, July.
    6. Gulan, Adam, 2018. "Paradise lost? A brief history of DSGE macroeconomics," Research Discussion Papers 22/2018, Bank of Finland.
    7. Hagenhoff, Tim & Lustenhouwer, Joep, 2020. "The role of stickiness, extrapolation and past consensus forecasts in macroeconomic expectations," BERG Working Paper Series 163, Bamberg University, Bamberg Economic Research Group.
    8. Nikolay Hristov & Markus Roth, 2019. "Uncertainty Shocks and Financial Crisis Indicators," CESifo Working Paper Series 7839, CESifo.
    9. Kubin, Ingrid & Zörner, Thomas O. & Gardini, Laura & Commendatore, Pasquale, 2019. "A credit cycle model with market sentiments," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 159-174.
    10. Saki Bigio & Eduardo Zilberman, 2020. "Speculation-Driven Business Cycles," Working Papers Central Bank of Chile 865, Central Bank of Chile.
    11. Luminita Stevens, 2020. "Coarse Pricing Policies," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 87(1), pages 420-453.
    12. Kollmann, Robert & Pataracchia, Beatrice & Raciborski, Rafal & Ratto, Marco & Roeger, Werner & Vogel, Lukas, 2016. "The post-crisis slump in the Euro Area and the US: Evidence from an estimated three-region DSGE model," European Economic Review, Elsevier, vol. 88(C), pages 21-41.
    13. Sergeyev, Dmitriy & Iovino, Luigi, 2018. "Central Bank Balance Sheet Policies Without Rational Expectations," CEPR Discussion Papers 13100, C.E.P.R. Discussion Papers.
    14. Cai, Michael & Del Negro, Marco & Giannoni, Marc P. & Gupta, Abhi & Li, Pearl & Moszkowski, Erica, 2019. "DSGE forecasts of the lost recovery," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1770-1789.
    15. Despina Gavresi & Anastasia Litina & Christos A. Makridis, 2021. "Split Personalities? Behavioral Effects of Temperature on Financial Decision-making," Discussion Paper Series 2021_16, Department of Economics, University of Macedonia, revised Nov 2021.
    16. Greg Howard & Carl Liebersohn, 2019. "What Explains U.S. House Prices? Regional Income Divergence," 2019 Meeting Papers 1054, Society for Economic Dynamics.
    17. Ferrante, Francesco, 2019. "Risky lending, bank leverage and unconventional monetary policy," Journal of Monetary Economics, Elsevier, vol. 101(C), pages 100-127.
    18. Yan Carrière-Swallow & José Marzluf, 2023. "Macrofinancial Causes of Optimism in Growth Forecasts," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(2), pages 509-537, June.
    19. Gric, Zuzana & Ehrenbergerova, Dominika & Hodula, Martin, 2022. "The power of sentiment: Irrational beliefs of households and consumer loan dynamics," Journal of Financial Stability, Elsevier, vol. 59(C).
    20. Mitsuru Katagiri, 2016. "Forward Guidance as a Monetary Policy Rule," Bank of Japan Working Paper Series 16-E-6, Bank of Japan.
    21. John Geanakoplos, 2022. "Leverage Cycle Theory of Economic Crises and Booms," Cowles Foundation Discussion Papers 2370, Cowles Foundation for Research in Economics, Yale University.

    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:gam:jjrfmx:v:16:y:2023:i:3:p:140-:d:1075564. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.