Uncertainty in Firm Valuation and a Cross-Sectional Misvaluation Measure

Abstract

In valuation analysis, the degree of uncertainty associated with the value of a company
is as important as the value itself. We propose an original and robust methodology for
company market valuation which replaces the traditional point estimate of the conventional
Discounted Cash Flow model with a probability distribution of fair values that conveys
information about both the expected value of the company and its intrinsic uncertainty.
Our methodology depends on two main ingredients: an econometric model for the company
revenues and a set of firm-specific balance sheet relations that are estimated using historical data. We explore the effectiveness and scope of our methodology through a series of
statistical exercises on publicly traded U.S. companies. At firm level, we show that the
fair value distribution derived with our methodology constitutes a reliable predictor of company’s future abnormal returns. At market level, we show that a long-short valuation (LSV)
factor, built using buy-sell recommendations based on the fair value distribution, contains
information not accessible through traditional market factors. The LSV factor increases
significantly the explanatory and predictive power of factor models estimated on portfolios
and individual stocks returns.

Keywords: Stochastic Discounted Cash Flow, Valuation Uncertainty, Valuation Factor, Kalman Filter.

JEL Classification: G11, G17, G32.