Updating Value Signals and Adding Momentum to Factor Models

Summary

This research summary examines why the Fama-French five-factor model may omit useful information. It argues that adding momentum produces a stronger explanatory and investment framework, then addresses why the traditional book-to-market value factor can appear redundant when profitability and investment factors are included. The proposed adjustment keeps book values subject to publication lags but updates the price used to calculate value, making the measure more responsive to current market prices. The article explains that this timely value measure can capture recent price declines and preserve its natural negative relationship with momentum.

The evidence described consists of factor regressions using US equity returns from 1963 through 2013, with reported intercepts and statistical tests. The account says the updated value measure, combined with momentum, improves the role of value and makes the investment factor appear less essential in the resulting model. These are historical findings, not a guarantee of future returns. The source also notes possible alternative explanations and says factor-model design remains unsettled; it does not provide enough implementation detail here to assess trading costs or out-of-sample performance.

Key ideas

• The article argues that momentum should be included when evaluating the Fama-French five-factor model.
• Updating prices while respecting accounting-data publication lags makes book-to-price value signals more timely.
• Traditional value and momentum tend to be negatively related, which may strengthen a combined portfolio.
• The reported historical regressions suggest timely value and momentum reduce the apparent incremental role of the investment factor.
• The findings are model- and sample-dependent, and the source identifies factor selection as ongoing research.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.