IDEAS home Printed from https://ideas.repec.org/a/spr/sjobre/v64y2012i6d10.1007_bf03372869.html
   My bibliography  Save this article

Der Basiszinssatz in der Praxis der Unternehmensbewertung: Quantifizierung eines systematischen Bewertungsfehlers

Author

Listed:
  • Moritz Bassemir

    (Goethe-Universität Frankfurt)

  • Günther Gebhardt

    (Goethe-Universität Frankfurt)

  • Sascha Leyh

    (Goethe-Universität Frankfurt)

Abstract

Zusammenfassung Das Ziel dieses Beitrages besteht in der Quantifizierung systematischer Bewertungsdifferenzen, die aus der Anwendung der vom IDW empfohlenen Methode zur Ableitung eines laufzeitkonstanten Basiszinssatzes resultieren. Hierzu berechnen wir die Unternehmenswerte aus 65 öffentlich verfügbaren Bewertungsgutachten unter Ver- wendung stichtagsbezogener Zinsstrukturdaten (laufzeitspezifische Spot Rates und implizite Forward Rates) neu. Die Ergebnisse zeigen statistisch und ökonomisch signifikante Abweichungen zwischen dem gutachtlichen und dem von uns ermittelten Unternehmenswert. Diese betragen im arithmetischen Mittel (Median) 3,09% (1,51%) und in absoluten Beträgen im Mittelwert (Median) 277 (3) Mio. Euro. Unsere Resultate zeigen, dass in der gängigen Praxis mit den Argumenten einer Komplexitätsreduktion und einer ausreichenden Präzision vermeidbare Bewertungsfehler in Kauf genommen werden.

Suggested Citation

  • Moritz Bassemir & Günther Gebhardt & Sascha Leyh, 2012. "Der Basiszinssatz in der Praxis der Unternehmensbewertung: Quantifizierung eines systematischen Bewertungsfehlers," Schmalenbach Journal of Business Research, Springer, vol. 64(6), pages 655-678, September.
    • Handle: RePEc:spr:sjobre:v:64:y:2012:i:6:d:10.1007_bf03372869
    DOI: 10.1007/BF03372869
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/BF03372869
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1007/BF03372869?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Holger Daske & Moritz Bassemir & Felix F. Fischer & Günther Gebhardt, 2010. "Manipulation des Börsenkurses durch gezielte Informationspolitik im Rahmen von Squeeze-Outs? — Eine empirische Untersuchung am deutschen Kapitalmarkt," Schmalenbach Journal of Business Research, Springer, vol. 62(3), pages 254-288, May.
    2. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-489, 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. Kearney, Fearghal & Shang, Han Lin & Sheenan, Lisa, 2019. "Implied volatility surface predictability: The case of commodity markets," Journal of Banking & Finance, Elsevier, vol. 108(C).
    2. Eric Hillebrand & Huiyu Huang & Tae-Hwy Lee & Canlin Li, 2018. "Using the Entire Yield Curve in Forecasting Output and Inflation," Econometrics, MDPI, vol. 6(3), pages 1-27, August.
    3. Matsumura, Marco & Moreira, Ajax & Vicente, José, 2011. "Forecasting the yield curve with linear factor models," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 237-243.
    4. Lin, Bing-Huei, 1999. "Fitting the term structure of interest rates for Taiwanese government bonds," Journal of Multinational Financial Management, Elsevier, vol. 9(3-4), pages 331-352, November.
    5. Plat, Richard, 2009. "Stochastic portfolio specific mortality and the quantification of mortality basis risk," Insurance: Mathematics and Economics, Elsevier, vol. 45(1), pages 123-132, August.
    6. Lily Y. Liu, 2017. "Estimating Loss Given Default from CDS under Weak Identification," Supervisory Research and Analysis Working Papers RPA 17-1, Federal Reserve Bank of Boston.
    7. Chiarella, Carl & Kang, Boda & Nikitopoulos, Christina Sklibosios & Tô, Thuy-Duong, 2013. "Humps in the volatility structure of the crude oil futures market: New evidence," Energy Economics, Elsevier, vol. 40(C), pages 989-1000.
    8. Sergio Zúñiga, 1999. "Modelos de Tasas de Interés en Chile: Una Revisión," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 36(108), pages 875-893.
    9. Detlefsen, Kai & Härdle, Wolfgang Karl, 2006. "Forecasting the term structure of variance swaps," SFB 649 Discussion Papers 2006-052, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. Evangelos Salachas & Georgios P. Kouretas & Nikiforos T. Laopodis, 2024. "The term structure of interest rates and economic activity: Evidence from the COVID‐19 pandemic," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 1018-1041, July.
    11. Mehmet Pasaogullari & Simeon Tsonevy, 2011. "The term structure of inflation compensation in the nominal yield curve," Working Papers (Old Series) 1133, Federal Reserve Bank of Cleveland.
    12. Pongsak Luangaram & Yuthana Sethapramote, 2016. "Central Bank Communication and Monetary Policy Effectiveness: Evidence from Thailand," PIER Discussion Papers 20, Puey Ungphakorn Institute for Economic Research.
    13. Bowsher, Clive G. & Meeks, Roland, 2008. "The Dynamics of Economic Functions: Modeling and Forecasting the Yield Curve," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1419-1437.
    14. Victor Lapshin, 2019. "A Nonparametric Approach to Bond Portfolio Immunization," Mathematics, MDPI, vol. 7(11), pages 1-12, November.
    15. Dick Dijk & Siem Jan Koopman & Michel Wel & Jonathan H. Wright, 2014. "Forecasting interest rates with shifting endpoints," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 693-712, August.
    16. repec:hum:wpaper:sfb649dp2017-027 is not listed on IDEAS
    17. Pagliari, Maria Sole, 2024. "Does one (unconventional) size fit all? Effects of the ECB’s unconventional monetary policies on the euro area economies," European Economic Review, Elsevier, vol. 168(C).
    18. Gary S. Anderson & Alena Audzeyeva, 2019. "A Coherent Framework for Predicting Emerging Market Credit Spreads with Support Vector Regression," Finance and Economics Discussion Series 2019-074, Board of Governors of the Federal Reserve System (U.S.).
    19. Norman R. Swanson & Weiqi Xiong, 2018. "Big data analytics in economics: What have we learned so far, and where should we go from here?," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 51(3), pages 695-746, August.
    20. João Frois Caldeira & Rangan Gupta & Muhammad Tahir Suleman & Hudson S. Torrent, 2021. "Forecasting the Term Structure of Interest Rates of the BRICS: Evidence from a Nonparametric Functional Data Analysis," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(15), pages 4312-4329, December.
    21. Liu, Yan & Wu, Jing Cynthia, 2021. "Reconstructing the yield curve," Journal of Financial Economics, Elsevier, vol. 142(3), pages 1395-1425.

    More about this item

    Keywords

    G10; G32; K22; M41;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • K22 - Law and Economics - - Regulation and Business Law - - - Business and Securities Law
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting

    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:spr:sjobre:v:64:y:2012:i:6:d:10.1007_bf03372869. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.