Fundamental Anomalies
Erica X. N. Li, Guoliang Ma, Shujing Wang, Cindy Yu
Management Science · 2026 · Volume 72 · Issue 2
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 a previous 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 with 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. This paper was accepted by Lukas Schmid, finance. Funding: S. Wang acknowledges financial support from the National Natural Science Foundation of China [Grants 72373110 and 71902140] and the Fundamental Research Funds for the Central Universities in China. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.01313 .
Keywords
q-theory, Bayesian MCMC estimation, anomalies, investment, profitability
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