A complex, rule-based, daily-rebalanced strategy that seeks upside in equities using momentum and trend signals (RSI, moving averages) while applying volatility/anti-beta hedges to limit risk; trades a wide set of ETFs.

What this strategy does, in plain language: It scans a bunch of well-known stock funds (tickers like SPY for the S&P 500, QQQ for big tech, etc.) and checks whether each one looks strong (is it trading above its recent average and rising) or expensive (is it in danger of a pullback). If conditions look good, it buys more of the strongest performers. If conditions look risky or overbought, it adds hedges that go up when fear rises (via volatility proxies like VIX-related ETFs and anti-volatility funds) to limit losses. There are several sub-strategies (like a treasury-momentum module and a “TINA” regime) that switch the mix between long positions and hedges based on different signals. RSI and moving-average checks are the core signals; the system also uses top-1 or top-N filters to pick the best ideas each day. In short: it tries to ride uptrends but stay protected when markets get noisy or expensive, using a broad family of ETFs to implement the rules daily.

A disciplined, hedge-enabled momentum strategy across a broad ETF universe. In out-of-sample tests it delivers solid risk-adjusted performance (Sharpe ~0.56, Calmar ~0.59) and 12.6% annualized return with built-in hedges for volatility.