The strategy uses a weekly momentum screen on AI-related stocks (top 3) and AI/tech ETFs (top 2), with a 75/25 split and equal weighting inside each group, rebalanced weekly for an AI-focused, momentum-driven exposure.

Description in plain language: 1) Build two mini-hundreds-of-assets universes: one of AI-related stocks (10 names) and one of AI/tech ETFs (5 funds). 2) For each asset, look back about 3 months and see how much money you would have made holding it (simplified: momentum over 90 days). Rank assets in each group from best to worst. 3) In the stock group, take the top 3 names. In the ETF group, take the top 2 funds. 4) Allocate 75% of your money to the stock group and 25% to the ETF group. Within the stock group, split that 75% evenly among the three chosen stocks. Within the ETF group, split the 25% evenly between the two chosen ETFs. 5) Rebalance every week: recalculate momentum, reselect the top assets, and adjust holdings to keep the 75/25 split with equal weighting inside each group. 6) What you’re getting: a tilt toward AI leadership with a built-in diversification through AI/tech ETFs, aiming to ride the trend while keeping a reasonable spread of exposure across AI hardware, software, and semiconductors. It’s a momentum-style approach, so it will tend to buy assets that have been outperforming recently and may rotate out of laggards. Notes: This description focuses on how the logic works in simple terms and assumes equal weights within each group unless otherwise specified by the actual implementation.

AI momentum strategy: superior out-of-sample performance—Sharpe ~2.06 vs SPY ~1.01, annualized return ~82% vs ~12.6%, Calmar ~6.6. Combines top AI stocks with AI/tech ETFs and weekly rebalancing for focused upside with disciplined risk.