Meta analiza rešitev za vrednotenje podjetij – so metode, ki temeljijo na umetni inteligenci, boljše?
DOI:
https://doi.org/10.32015/JIBM.2024.16.2.6Ključne besede:
vrednotenje podjetij, tradicionalne in sodobne metode vrednotenja, strojno učenje, nevronske mreže, umetna inteligencaPovzetek
Namen članka – članek obravnava izziv natančnega ocenjevanja vrednosti podjetja v današnjem dinamičnem okolju ter raziskuje omejitve tradicionalnih metod vrednotenja in možnosti sodobnih, tehnološko zasnovanih pristopov.
Metodologija raziskave – v študiji so za pregled različnih tehnik vrednotenja podjetij uporabljene kvalitativne raziskovalne metode, vključno z analizo vsebine, deduktivnim sklepanjem in primerjalno analizo.
Ugotovitve – raziskava ugotavlja, da so tradicionalne metode, kot sta diskontirani denarni tok in relativno vrednotenje, zastarele in ne zajemajo vseh dejavnikov vrednosti. Sodobni pristopi, kot so vrednotenje na podlagi simulacij, strojno učenje in nevronske mreže, združujejo tradicionalne metode z naprednimi tehnikami. Te metodologije uporabljajo obsežne nabore podatkov in izpopolnjene algoritme, kar povečuje natančnost napovedovanja in razumevanje tržne dinamike. Zlasti nevronske mreže so odlične pri analiziranju zapletenih vzorcev in prilagajanju spremembam na trgu. Vendar nobena metoda ne more zajeti vseh nians, kar zahteva različne pristope in priznavanje subjektivne narave vrednotenja.
Praktični doprinos – ugotovitve kažejo, da je mogoče z uporabo naprednih metodologij izboljšati vrednotenje podjetij, kar vodi k boljšemu sprejemanju odločitev ter boljšemu razumevanju tržne dinamike in notranje vrednosti.
Izvirnost/vrednost – ta študija edinstveno preučuje prehod s tradicionalnih na sodobne metode vrednotenja, pri čemer poudarja boljšo učinkovitost nevronskih mrež in potrebo po večplastnem pristopu k vrednotenju podjetij.
Literatura
Azungah, T. (2018). Qualitative research: deductive and inductive approaches to data analysis. Qualitative Research Journal, 18(4), 383–400. https://doi.org/10.1108/QRJ-D-18-00035
Bakarich, K. M., Hossain, M., & Weintrop, J. (2019). Different time, different tone: Company life cycle. Journal of Contemporary Accounting and Economics, 15(1), 69–86. https://doi.org/10.1016/j.jcae.2018.12.002
Basole, R. C., Russell, M. G., Huhtamäki, J., Rubens, N., Still, K., & Park, H. (2015). Understanding business ecosystem dynamics: A data-driven approach. ACM Transactions on Management Information Systems, 6(2). https://doi.org/10.1145/2724730
Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40. https://doi.org/10.3316/QRJ0902027
Carson, R. T., & Hanemann, W. M. (2005). Chapter 17 Contingent Valuation. Handbook of Environmental Economics, 2, 821–936. https://doi.org/10.1016/S1574-0099(05)02017-6
Chen, A. H.-L., Lee, Z.-H., & Wang, X. (2012). The Valuation of Firms in Taiwan’s Biotech Industry. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.1928078
Damodaran, A. (2002). Investment Valuation: Tools and Techniques for Determining the Value of Any Asset (3rd ed.). John Wiley and Sons. https://suhaplanner.files.wordpress.com/2018/09/investment-valuation-3rd-edition.pdf
Damodaran, A. (2007). Valuation approaches and metrics: A survey of the theory and evidence. Foundations and Trends in Finance, 1(8), 693–784. https://doi.org/10.1561/0500000013
Denzin, N. K. (1970). The research act: A theoretical introduction to sociological methods. New York: Aldine.
Dhochak, M., Pahal, S., & Doliya, P. (2022). Predicting the Startup Valuation: A deep learning approach. Venture Capital. https://doi.org/10.1080/13691066.2022.2161968
Dunleavy, P. G. (2009). Reorganization or Liquidation? American Bankruptcy Institute Journal, 28(6), 56-57,88.
Fazzini, M. (2018). Value, Valuation, and Valuer. Business Valuation, 1–22. https://doi.org/10.1007/978-3-319-89494-2_1
Fernández, P. (2007). Company valuation methods. The most common errors in valuations. https://d1wqtxts1xzle7.cloudfront.net/36234952/COMMON_ERRORS_IN_VALUATION-libre.pdf?1421037150=&response-content-disposition=inline%3B+filename%3DCOMMON_ERRORS_IN_VALUATION.pdf&Expires=1711028303&Signature=Xp4oSFVZIXuNmWEBvhSBd5IBuOYgP1vekAvB1KpvCKRquFnYk
Geertsema, P., & Lu, H. (2023). Relative Valuation with Machine Learning. Journal of Accounting Research, 61(1), 329–376. https://doi.org/10.1111/1475-679X.12464
Glaser, B. G., & Strauss, A. L. (2017). Discovery of grounded theory: Strategies for qualitative research. Discovery of Grounded Theory: Strategies for Qualitative Research, 1–271. https://doi.org/10.4324/9780203793206
Guner, P. U., & Unal, S. N. (2023). An artificial neural network based method for company valuation. Pressacademia. https://doi.org/10.17261/pressacademia.2023.1741
Haich, A. P. (2021). DEEP LEARNING APPLIED TO PUBLIC COMPANY VALUATION FOR VALUE INVESTING.
Harwood, T. G., & Garry, T. (2003). An overview of content analysis. In Westburn Publishers Ltd (Vol. 3, Issue 4). https://doi.org/https://doi.org/10.1362/146934703771910080
Hausman, J. (2012). Contingent valuation: From dubious to hopeless. Journal of Economic Perspectives, 26(4), 43–56. https://doi.org/10.1257/jep.26.4.43
Hoff, J. M., Larose, L. A., & Scaturro, F. J. (2002). Public Companies. Law Journal Press.
Holder, L., Gruenbichler, R., & Grbenic, S. O. (2022). The use of artificial intelligence in business valuation: Status quo and trends based on a literature review. https://graz.elsevierpure.com/en/publications/the-use-of-artificial-intelligence-in-business-valuation-status-q
Hoyos, D., & Mariel, P. (2010). Contingent valuation: Past, present and future. Prague Economic Papers, 4, 329–343. https://doi.org/10.18267/j.pep.380
Hu, X., Sy, M. O., & Wu, L. (2021). A Factor Model of Company Relative Valuation. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3706995
Hudson, J. (1986). An analysis of company liquidations. Applied Economics, 18(2), 219–235. https://doi.org/10.1080/00036848600000025
Isik, Y. (2010). AN OVERVIEW OF COMPANY VALUATION TECHNIQUES AND AN APPLICATION.
Jagrič, T., Fister, D., Grbenic, S. O., & Herman, A. (2024). Private Firm Valuation Using Multiples: Can Artificial Intelligence Algorithms Learn Better Peer Groups? Information, 15(6), 305. https://doi.org/10.3390/info15060305
Johnson-Laird, P. (2010). Deductive reasoning. Wiley Interdisciplinary Reviews: Cognitive Science, 1(1), 8–17. https://doi.org/10.1002/wcs.20
Kaunisto, L. (2024). Estimating private company financial figures in early-phase M&A: A machine learning approach.
Koklev, P. (2023). Prerequisites for the Use of Machine Learning for Business Valuation. Relacoes Internacionais No Mundo Atual, 6(39). https://doi.org/10.21902/Revrima.v6i39.6267
Koklev, P. S. (2022). Business Valuation with Machine Learning. Finance: Theory and Practice, 26(5), 132–148. https://doi.org/10.26794/2587-5671-2022-26-5-132-148
Kruschwitz, L., & Loeffler, A. (2006). Discounted Cash Flow: A Theory of the Valuation of Firms. John Wiley and Sons. https://books.google.si/books?hl=sl&lr=&id=mWM9b6gDVi0C&oi=fnd&pg=PR5&dq=discounted+cash+flow&ots=0q1lFCCjHA&sig=iJYphwkfs3WLaRV6BpPBPEAxB6U&redir_esc=y#v=onepage&q=discounted cash flow&f=false
Kulwizira Lukanima, B. (2023a). An Overview of Corporate Valuation. In Corporate Valuation A Practical Approach with Case Studies (pp. 3–24). https://doi.org/10.1007/978-3-031-28267-6_1
Kulwizira Lukanima, B. (2023b). An Overview of Relative Valuation. In Corporate Valuation A Practical Approach with Case Studies (pp. 613–633). https://doi.org/10.1007/978-3-031-28267-6_19
Kulwizira Lukanima, B. (2023c). Corporate Valuation A Practical Approach with Case Studies. Springer Cham. https://doi.org/https://doi.org/10.1007/978-3-031-28267-6
Kulwizira Lukanima, B. (2023d). Dividend Discount Models. In Corporate Valuation A Practical Approach with Case Studies (pp. 559–583). https://doi.org/10.1007/978-3-031-28267-6_17
Kulwizira Lukanima, B. (2023e). Free Cash Flow Discount Models: Cost of Capital Approach. In Corporate Valuation A Practical Approach with Case Studies (pp. 483–540). https://doi.org/10.1007/978-3-031-28267-6_15
Kulwizira Lukanima, B. (2023f). Free Cash Flow Discount Models: The Adjusted Present Value Approach. In Corporate Valuation A Practical Approach with Case Studies (pp. 541–557). https://doi.org/10.1007/978-3-031-28267-6_16
Kulwizira Lukanima, B. (2023g). Further Issues with Cash Flow Discount Models. In Corporate Valuation A Practical Approach with Case Studies (pp. 585–609). https://doi.org/10.1007/978-3-031-28267-6_18
Leifer, I., & Lev, L. (2016). Small business valuation with use of cash flow stochastic modeling. Proceedings - 2nd International Symposium on Stochastic Models in Reliability Engineering, Life Science, and Operations Management, SMRLO 2016, 511–516. https://doi.org/10.1109/SMRLO.2016.90
Liu, M., Shen, Y., Tang, J., & Li, X. (2020). Research on valuation system of listed companies based on neural network model. Proceedings - 2020 International Conference on Virtual Reality and Intelligent Systems, ICVRIS 2020, 1120–1123. https://doi.org/10.1109/ICVRIS51417.2020.00273
Matschke, M. J., Brösel, G., & Matschke, X. (2010). Fundamentals of functional business valuation. Journal of Business Valuation and Economic Loss Analysis, 5(1). https://doi.org/10.2202/1932-9156.1097
Mukhlynina, L., & Nyborg, K. G. (2016). The Choice of Valuation Techniques in Practice: Education versus Profession. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2784850
Myers, M. D. (2020). Qualitative Research in Business and Management (Third). SAGE Publications Ltd.
Nenkov, D., & Hristozov, Y. (2022). DCF Valuation of Companies: Exploring the Interrelation Between Revenue and Operating Expenditures. Economic Alternatives, 28(4), 626–646. https://doi.org/10.37075/EA.2022.4.04
Nissim, D. (2013). Relative valuation of U.S. insurance companies. Review of Accounting Studies, 18(2), 324–359. https://doi.org/10.1007/s11142-012-9213-8
Nyborg, K. G., & Mukhlynina, L. (2016). Survey of Valuation Professionals: Valuation Techniques in Practice.
Oh, S.-J. (2021). Analysis of the Valuation Model for the state-of-the-art ICT Technology. The Journal of the Convergence on Culture Technology, 7(4), 705–710. https://doi.org/https://doi.org/10.17703/JCCT.2021.7.4.705
Öhrner, M., & Öhman, O. (2023). Relative or Discounted Cash Flow Valuation on the Fifty Largest US-Based Corporations on Nasdaq : Which of these valuation methods provides the most accurate valuation forecast?
Onwuegbuzie, A. J., Leech, N. L., & Collins, K. M. T. (2012). Qualitative Analysis Techniques for the Review of the Literature. The Qualitative Report, 17. https://eric.ed.gov/?id=EJ981457
Pétursson, E. (2016). Relative Valuation – Accuracy of Corporate Valuation Using Multiples.
Pienaar, P. T. (2015). The use of the Discounted Cash Flow (DCF) method as a method of valuation within the South African property industry: A critical review.
Sharma, M., & Prashar, E. (2013). A Conceptual Framework for Relative Valuation. The Journal of Private Equity, 16(3), 29–32.
Sherman, A. (2010). Mergers and Acquisitions from A to Z. AMACOM.
Siddiaui, S. S., & Patil, V. A. (2018). Stock Market Valuation using Monte Carlo Simulation. Proceedings of the 2018 International Conference on Current Trends towards Converging Technologies, ICCTCT 2018. https://doi.org/10.1109/ICCTCT.2018.8550864
Sterling, R. R. (1968). The Going Concern: An Examination. The Accounting Review, 43(3), 481–502.
Strašek, S., & Jagrič, T. (2008). Borzni trgi.
Strauss, A. L., & Corbin, J. M. (1998). Basics of Qualitative Research : Techniques and Procedures for Developing Grounded Theory. Sage Publications, Inc. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=18c7cfe7a46c7771b60dc384b1b4e350f65b13e2
Torrez, J. G., Al-Jafari, M., & Juma’h, A. (2018). Corporate Valuation: A Literature Review. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3165643
Vayas-Ortega, G., Soguero-Ruiz, C., Rodríguez-Ibáñez, M., Rojo-Álvarez, J. L., & Gimeno-Blanes, F. J. (2020). On the differential analysis of enterprise valuation methods as a guideline for unlisted companies assessment (II): Applying machine-learning techniques for unbiased enterprise value assessment. Applied Sciences (Switzerland), 10(15). https://doi.org/10.3390/APP10155334
Venkatachalam, L. (2004). The contingent valuation method: A review. Environmental Impact Assessment Review, 24(1), 89–124. https://doi.org/10.1016/S0195-9255(03)00138-0
Wilimowska, Z., & Krzysztoszek, T. (2013). The use of artificial neural networks in company valuation process. Studies in Computational Intelligence, 457, 279–288. https://doi.org/10.1007/978-3-642-34300-1_27
Yang, Y., Yang, J. Q., Bao, R., Zhan, D. C., Zhu, H., Gao, X. R., Xiong, H., & Yang, J. (2023). Corporate Relative Valuation Using Heterogeneous Multi-Modal Graph Neural Network. IEEE Transactions on Knowledge and Data Engineering, 35(1), 211–224. https://doi.org/10.1109/TKDE.2021.3080293
Prenosi
Objavljeno
Številka
Rubrika
Licenca
Avtorske pravice so zaščitene s Creative Commons Priznanje avtorstva-Deljenje pod enakimi pogoji 4.0 Mednarodna CC BY-SA 4.0 in jih avtorji ohranijo v okviru te licence. Za objavo svojega članka, vključno s povzetkom, prenesejo avtorji avtorske oz. licenčne pravice na revijo MIP = JIBM. To nam omogoča popolno zaščito avtorskih pravic ter razširjanje članka in revije MIP=JIBM v najširši možni krog bralcev revije v elektronski obliki. Avtorji so sami odgovorni za pridobitev dovoljenja za razmnoževanje avtorskega gradiva iz drugih virov.
