Systematic ETF Relative-Strength Strategy & Alpha Attribution I built this project to answer a fairly narrow question: can a simple relative-strength rule rotate among liquid commodity and industry ETFs, and how much of the resulting return is actually unexplained alpha? The backtest looked attractive at first. The attribution work changed the conclusion. Standard Fama-French controls left a positive intercept, but adding direct proxies for the exposures the strategy was trading raised model R² from 14.0% to 63.6% and reduced the annualized intercept from 16.5% to 0.38%. My final interpretation is therefore a rules-based way to manage commodity and industry exposure, not evidence of persistent standalone alpha. Strategy The candidate set is GLD, SLV, USO, SMH, and XBI; SPY is used only as the comparator. For ETF \(i\) on date \(t\), the signal is its 20-session adjusted return less the corresponding SPY return: $$ RS{i,t}^{20}=\left(\frac{P{i,t}}{P{i,t-20}}-1\right)-\left(\frac{P{SPY,t}}{P{SPY,t-20}}-1\right). $$ At each rebalance, the two highest finite signals receive 2.5% sleeves.

⚠ No verified equity curve — no track-record source connected.

No score history is stored yet — only the current score is shown.

⚠ No live verification account connected — ask for proof before buying.

Alerts on changes: coming soon

Prop-firm compatibility not provided.

Data-completeness & trust index (not a profitability rating)