Equity Valuation and Fundamental Analysis: to Bayes or not to Bayes?
43 Pages Posted: 28 Jun 2021 Last revised: 4 Sep 2021
Date Written: September 3, 2021
This paper discusses the benefits and drawbacks of adopting Bayesian inference for practical equity valuation and fundamental analysis and derives a decision-focused valuation model for investors. Despite the inevitably subjectivist (i.e. Bayesian) nature of equity valuation, almost all research contributions on the topic follow a frequentist approach. In this paper, I perform a methodological discussion on equity valuation from the perspective of a fundamental investor and provide a starting point for a more investor-oriented equity valuation in both theory and practice. I argue that valuation theory alone supplies enough information to generate suitable, normally distributed weakly informative priors for long-term speculative variables. When combined with maximum-likelihood estimates using historical fundamentals and short-term estimates, these simple-to-implement priors should lead to more reliable value estimates. Using the specified prior and likelihood, I propose a Bayesian algorithm for the simulation of the posterior distribution of intrinsic value.
Keywords: Bayesian Inference, Accounting, Equity Valuation, Fundamental Analysis, Intrinsic Value
JEL Classification: M41, G11, G12, G14, G17, G32
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