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Cited by 437

The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.

A Comparison of Dividend, Cash Flow, and Earnings Approaches to Equity Valuation*

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PENMAN, STEPHEN H., SOUGIANNIS, THEODORE·1998·Contemporary Accounting Research
DOI 10.1111/j.1911-3846.1998.tb00564.x
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Abstract

Standard formulas for valuing the equity of going concerns require forecasting payoffs to infinity but practical analysis requires that payoffs be forecasted over finite horizons. This truncation inevitably involves often‐troublesome terminal value calculations. This paper contrasts dividend discount techniques, discounted cash flow analysis, and techniques based on accrual earnings when each is applied with finite‐horizon forecasts. Valuations based on average ex post payoffs over various horizons, with and without terminal value calculations, are compared with ex ante market prices to discover the error introduced by each technique in truncating the horizon. Valuation errors are lower using accrual earnings techniques rather than cash flow and dividend discounting techniques. The accounting features that make a given technique less than ideal for finite horizon analysis are also detailed. Conditions where a given technique requires particularly long forecasting horizons are identified and the performance of the alternative techniques under those conditions is examined.

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Crossref · 10.1111/j.1911-3846.1998.tb00564.x

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Metadata

Authors
PENMAN, S. H., & SOUGIANNIS, T.
Venue
Contemporary Accounting Research
Publisher
Wiley
Published
1998-09
Volume
15
Issue
3
Pages
343-383
ISSN
  • 0823-9150 (ISSN-L)
  • 1911-3846
DOI
10.1111/j.1911-3846.1998.tb00564.x
OpenAlex
W4246406111
Cited by
437
References
19
FWCI
74.29
Type
journal article
Language
en
Open access
green

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PENMAN, S. H., & SOUGIANNIS, T. (1998). A Comparison of Dividend, Cash Flow, and Earnings Approaches to Equity Valuation*. Contemporary Accounting Research. https://doi.org/10.1111/j.1911-3846.1998.tb00564.x

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.