The academic literature literally contains hundreds of variables that seem to predict the cross-section of expected returns. This so-called ‘anomaly zoo’ has caused many to question whether researchers are using the right tests of statistical significance. But, here’s the thing: even if researchers use the right tests, they will still draw the wrong conclusions from their econometric analyses if they start out with the wrong priors—i.e., if they start out with incorrect beliefs about the ex ante probability of encountering a tradable anomaly.

So, what are the right priors? What is the correct anomaly base rate?

We develop a first way to estimate the anomaly base rate by combining two key insights: #1) Empirical-Bayes methods capture the implicit process by which researchers form priors based on their past experience with other variables in the anomaly zoo. #2) Under certain conditions, there is a one-to-one mapping between these prior beliefs and the best-fit tuning parameter in a penalized regression. We study trading-strategy performance to verify our estimation results. If you trade on two variables with similar one-month-ahead return forecasts in different anomaly-base-rate regimes (low vs. high), the variable in the low base-rate regime consistently underperforms the otherwise identical variable in the high base-rate regime.

More Research From These Scholars

BFI Working Paper Jul 30, 2018

Dissecting Characteristics Nonparametrically

Joachim Freyberger, Andreas Neuhierl, Michael Weber
Topics:  Fiscal Studies, Financial Markets
BFI Working Paper Jul 31, 2019

The Propagation of Monetary Policy Shocks in a Heterogeneous Production Economy

Ernesto Pasten, Raphael Schoenle, Michael Weber
Topics:  Monetary Policy, Fiscal Studies
BFI Working Paper Aug 3, 2018

Price Rigidity and the Origins of Aggregate Fluctuations

Ernesto Pasten, Raphael Schoenle, Michael Weber
Topics:  Fiscal Studies, Monetary Policy