Fundamental Anomalies

Abstract

This paper proposes a portfolio-independent method to estimate q-theory models, in which

parameters are obtained using Bayesian Markov Chain Monte Carlo (MCMC) to match

firm-level stock returns. Our methodology addresses Campbell’s (2017) critique on prior

studies that model parameters are chosen to fit a specific set of anomalies and different values

are needed to fit each anomaly. By targeting the entire sample of firm-level returns and

allowing industry and time variations in parameter values, our estimations yield higher

correlations between realized and fundamental portfolio returns compared to prior literature.

Additionally, the estimated two-capital model generates large and significant size, momentum,

profitability, investment, and intangibles premiums, but falls short in explaining the value and

accruals anomalies. This limitation underscores the importance of portfolio-independent

parameter estimation in evaluating a model’s capability to generate return anomalies.

Keywords: q-theory, Bayesian MCMC estimation, Anomalies, Investment, Profitability

JEL Classification: D21, D92, E22, E44, G12, G14, G31, G32, G34