Quant factor performance can vary greatly over time, and recent research by the StarMine quant research team at Thomson Reuters shows that returns from a multi-factor quant strategy can be enhanced by using macroeconomic data to derive time varying factor weights. The research shows that factors haven’t stopped working – rather we need to understand the conditions in which they do and do not work well.

Thomson Reuters Director of Quantitative Research Dr. Stephen Maliknak explained how quants can use dynamic factor weighting to enhance their strategies in a recent webcast, Enhancing Quant Strategies with Dynamic Factor Weighting. Access a recording of the webcast via the link above, or download the research note here: Factor Timing in U.S. Equities.

The figure below shows that a factor timing strategy outperforms a baseline static model. The investment universe is comprised of the top 98.5% of stocks by market cap in the U.S. (roughly equivalent to the Russell 3000).

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