Valuation biases, error measures, and the conglomerate discount

Biases and error measures: how to compare valuation methods

Ingolf Dittmann and Ernst Maug

No 07-37, Papers from Sonderforschungsbreich 504

Abstract: We investigate biases of valuation methods and document that these depend largely on the choice of error measure (percentage vs. logarithmic errors) used to compare valuation procedures. We analyze four multiple valuation methods (averaging with the arithmetic mean, harmonic mean, median, and the geometric mean) and three present value approaches (dividend discount model, discounted cash flow model, residual income model). Percentage errors generate a positive bias for most multiples, and they imply that setting company values equal to their book values often becomes the best valuation method. Logarithmic errors avoid unwanted consequences and imply that the median and the geometric mean are unbiased while the arithmetic mean is biased upward as much as the harmonic mean is biased downward. The dividend discount model dominates the DCF-model only for percentage errors, while the opposite is true for logarithmic errors. The residual income model is optimal for both error measures.

Keywords: Valuation; Financial Ratios; Multiples; Dividend Discount Model; Discounted Cash Flow Model; Residual Income Model (search for similar items in EconPapers)
JEL-codes: G10 G34 M41 (search for similar items in EconPapers)
Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://madoc.bib.uni-mannheim.de/2531/1/dp07_37.pdf

Related works:
Working Paper: Valuation Biases, Error Measures, and the Conglomerate Discount (2006)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:mnh:spaper:2531

Access Statistics for this paper

More papers in Papers from Sonderforschungsbreich 504 Contact information at EDIRC.
Bibliographic data for series maintained by Katharina Rautenberg ().