Measuring Equity Style Drift and Rotating Among Factor Strategies

Summary

This assignment analyzes how a stock selection strategy’s exposure to market styles changes over time, then outlines a framework for rotating among factor strategies. The initial analysis uses a small-capitalization selection factor and compares strategy returns with style-factor returns. It reports that market capitalization has the strongest overall relationship, followed by beta and liquidity, while the relative correlations vary across three market periods. A separate test using a machine-learning strategy also finds changing style exposure, especially in market capitalization and beta.

The proposed rotation framework calculates each candidate factor strategy’s returns over the preceding ten days, selects the strongest, and holds its chosen stock list for ten days before repeating. It also tracks factor performance and compares the strategy’s daily returns with style factors. The document gives no detailed performance figures, controls, or evidence that the rotation improves returns. Its period-based correlations and short lookback therefore describe a proposed approach, not proof of durable predictive power.

Key ideas

• A small-capitalization strategy can show changing correlations with market styles over time.
• The assignment reports market capitalization as its strongest overall style relationship, followed by beta and liquidity.
• A proposed rotation method selects the factor strategy with the highest return over the preceding ten days.
• The rotation framework holds the selected stock list for ten days before evaluating the factor strategies again.
• Comparing daily strategy returns with style-factor returns can help describe style alignment.

Tags

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