Monthly 12-Month Momentum Rotation Across Six Equity Styles

Summary

This QuantConnect algorithm ranks six U.S. equity style ETFs covering small-, mid-, and large-cap value and growth. It measures each ETF’s momentum over roughly twelve months of daily data, then takes a long position in the strongest style and a short position in the weakest. The portfolio is reconsidered monthly, with holdings in the middle-ranked styles liquidated.

The code specifies a starting date and cash balance, applies a custom transaction-fee model, and sets leverage on each security. It also skips trading the S&P 500 growth ETF in October 2020 to work around a stated data error. The document provides an implementation rather than performance results: it includes no return series, benchmark comparison, or risk analysis. Its backtest assumptions, including leverage, fees, shorting, and data handling, would need scrutiny before drawing conclusions about the strategy’s real-world viability.

Key ideas

• The strategy compares six U.S. equity style ETFs across value and growth categories and market-cap sizes.
• It uses approximately twelve months of daily momentum to rank the ETFs.
• At each monthly rebalance, it goes long the top-ranked ETF and short the bottom-ranked ETF.
• The implementation liquidates middle-ranked holdings and specifies leverage and transaction fees.
• A stated data issue causes the algorithm to skip the S&P 500 growth ETF in October 2020.

Tags

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