Adapting Trend Following to Turning Points with Fast and Slow Momentum

Summary

The research summary defines a trend turning point as a period when short-window and long-window time-series momentum signals point in opposite directions. It reports that more frequent turning points are associated with weaker risk-adjusted returns for static trend strategies, while turning-point frequency conveys information distinct from return volatility. The study’s historical sample covers equity indexes, bond markets, commodities, and currencies from 1971 through 2019.

Its dynamic approach classifies each market as a bull phase, correction, bear phase, or rebound, then adjusts the mix of fast and slow momentum using historical returns after corrections and rebounds. The reported portfolio results suggest this adaptation helped capture returns after turning points and outperformed a static 12-month trend strategy in the most recent decade of the sample. These findings are historical and based on the described portfolio construction; the summary does not provide full implementation equations or establish that the results persist out of sample or after trading costs.

Key ideas

• A turning point occurs when short- and long-window momentum signals disagree.
• The study reports a negative association between turning-point frequency and static trend strategy risk-adjusted performance.
• Turning-point frequency appears to provide information different from return volatility.
• The dynamic strategy classifies market states and changes the blend of fast and slow momentum based on historical post-correction and post-rebound returns.
• Reported historical results do not establish future performance or account fully for implementation costs.

Tags

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