Combining Market Anomalies and Refining Value-Momentum Factor Models

Summary

The document summarizes research on combining market anomalies and on refining multi-factor models. For anomaly strategies, it reports that returns to many well-known anomalies declined after academic publication, while diversified long-short portfolios holding several anomalies performed better than individual anomaly strategies on return and risk. A dynamic approach that allocates more to anomalies with stronger recent returns is described as outperforming equal weighting across historical periods and market conditions. The summary does not identify all 15 anomalies or provide detailed portfolio construction rules.

A longer discussion critiques the Fama-French five-factor model for omitting momentum and for using a lagged price in its book-to-market value measure. It describes updating the price input while retaining the accounting-data lag, then combining this more timely value signal with momentum. Historical US equity factor regressions are presented as evidence that this approach improves value’s role and may make the investment factor redundant. The results depend on historical samples and model choices; the document notes that alternative solutions and further factor research remain possible.

Key ideas

• Diversifying across multiple long-short anomaly portfolios is reported to improve return and risk relative to relying on a single anomaly.
• A dynamic strategy that favors anomalies with stronger recent returns is reported to outperform equal weighting historically.
• The document notes that anomaly performance often weakened after publication in academic literature.
• Adding momentum and using more current prices in the value measure can change the apparent contribution of other factors.
• The reported findings are historical and do not settle the best factor model or establish future performance.

Tags

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