Using PCA to Assess Smart Beta Strategy Diversity and Factor Exposure

Summary

The document describes a study of four MSCI smart beta equity indexes and a market weighted benchmark. It uses principal component analysis (PCA) to separate shared market movements from strategy specific components, then regresses those components on Fama French and Carhart factors to examine their return sources and overlap. The analysis covers U.S. data from 1999 through 2014 and compares results across global, EAFE, and emerging markets. The market component explains most index variation, while momentum has the clearest distinct component. Equal weighting and value weighting add relatively little distinct behavior to the benchmark portfolio; fundamental weighting shows a value tilt. Some components share momentum exposure, suggesting limited diversification among strategies. The study also reports that emerging market smart beta components have comparatively little explanatory weight. These findings depend on the selected indexes, sample period, and factor model; they describe historical relationships and do not establish future performance or universal suitability.

Key ideas

• PCA can separate common market returns from components associated with individual smart beta strategies.
• The market component explains most of the variation across the studied indexes.
• Momentum has a more distinct component, while equal weighting and value weighting contribute less differentiation from the benchmark.
• Overlapping factor exposures suggest that smart beta strategies may provide less diversification than their labels imply.
• The study finds weaker smart beta influence in emerging markets, limiting generalization from U.S. results.

Tags

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