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This study presents an industry-level comparison of multiples-based and flows-based
equity valuation models for a dataset of 1,251 unique firms from the United States, in
the period 2006-2011. The purpose is to investigate which model performs best, and if
there are significant differences across industries. Models are compared in terms of
signed and absolute prediction errors, as well as the explanatory power of their
estimates, vis-à-vis contemporaneous stock prices. Across industries, forward price-toearnings
and an abnormal earnings growth model with no terminal value are rated as the
models with best fit in predicting market prices, on a risk-adjusted basis. This analysis
is complemented with a robustness assessment of peer selection criteria, finding that
Coarsened Exact Matching (CEM) – a systematic and more refined approach to identify
comparable firms – yields superior results for multiples-based models than traditional
peer selection methods. Further, it allows for measuring of the level of firm proximity.
The study concludes by comparing theoretical results with models used in practice by
financial analysts in the United Kingdom, documenting inconclusive results for the two
sampled industries – pharmaceutical and utilities.
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Financial accounting Broker reports Equity valuation Multiples Residual income